PV162 Image Processing Project

Faculty of Informatics
Spring 2021
Extent and Intensity
0/2. 2 credit(s) (plus extra credits for completion). Type of Completion: k (colloquium).
Taught online.
Teacher(s)
doc. RNDr. Petr Matula, Ph.D. (lecturer)
doc. RNDr. David Svoboda, Ph.D. (seminar tutor)
doc. RNDr. Pavel Matula, Ph.D. (seminar tutor)
Dmitry Sorokin, Ph.D. (seminar tutor)
RNDr. Martin Maška, Ph.D. (seminar tutor)
prof. RNDr. Michal Kozubek, Ph.D. (seminar tutor)
Mgr. Karel Štěpka, Ph.D. (seminar tutor)
RNDr. Roman Stoklasa, Ph.D. (seminar tutor)
Guaranteed by
doc. RNDr. Petr Matula, Ph.D.
Department of Visual Computing - Faculty of Informatics
Supplier department: Department of Visual Computing - Faculty of Informatics
Prerequisites
SOUHLAS
Knowledge at the level of course PV131 or at least PB130 is required
Course Enrolment Limitations
The course is also offered to the students of the fields other than those the course is directly associated with.
The capacity limit for the course is 25 student(s).
Current registration and enrolment status: enrolled: 4/25, only registered: 0/25, only registered with preference (fields directly associated with the programme): 0/25
fields of study / plans the course is directly associated with
there are 74 fields of study the course is directly associated with, display
Course objectives
The course objective is to strengthen the student's capability of analyzing real-world problems in the field of digital image processing and finding suitable solutions.
Learning outcomes
At the end of the course the student will be able to better solve practical problems from the area of digital image processing.
Syllabus
  • Extension and more profound knowledge of the topics presented in PV131 and PB130 with emphasis on solving a practical project. The projects are in principle of three types:
  • Programming: implementation and testing of a given algorithm (in a chosen programming language)
  • Creative: finding a suitable solution to a given problem
  • Study: testing and comparison of several algorithms/implementations on a given data
Literature
  • Articles published in scientific journals and conference proceedings according to the specification of project leader.
Teaching methods
The student selects a topic from a given list or suggests own topic from the field of digital image processing. (S)he works independently and is supervised by one of the tutors. The results of the work are presented at the end of the semester to other students and tutors.
Assessment methods
To obtain credits, the student must finish the task (process data, write a fully functional computer program), give a presentation and discuss the results at a seminar.
Language of instruction
Czech
Follow-Up Courses
Further Comments
Study Materials
The course is taught annually.
The course is taught: every week.
Teacher's information
http://cbia.fi.muni.cz/
The course is also listed under the following terms Autumn 2004, Autumn 2005, Autumn 2006, Autumn 2007, Autumn 2008, Autumn 2009, Autumn 2010, Autumn 2011, Spring 2013, Autumn 2013, Spring 2014, Autumn 2014, Spring 2015, Autumn 2015, Spring 2016, Autumn 2016, Spring 2017, Autumn 2017, Spring 2018, Autumn 2018, Spring 2019, Autumn 2019, Spring 2020, Autumn 2020, Autumn 2021, Spring 2022.

PV162 Image Processing Project

Faculty of Informatics
Spring 2022
Extent and Intensity
0/2. 2 credit(s) (plus extra credits for completion). Type of Completion: k (colloquium).
Taught online.
Teacher(s)
doc. RNDr. Petr Matula, Ph.D. (lecturer)
doc. RNDr. David Svoboda, Ph.D. (seminar tutor)
doc. RNDr. Pavel Matula, Ph.D. (seminar tutor)
Dmitry Sorokin, Ph.D. (seminar tutor)
RNDr. Martin Maška, Ph.D. (seminar tutor)
prof. RNDr. Michal Kozubek, Ph.D. (seminar tutor)
Mgr. Karel Štěpka, Ph.D. (seminar tutor)
RNDr. Roman Stoklasa, Ph.D. (seminar tutor)
Guaranteed by
doc. RNDr. Petr Matula, Ph.D.
Department of Visual Computing - Faculty of Informatics
Supplier department: Department of Visual Computing - Faculty of Informatics
Prerequisites
SOUHLAS
Knowledge at the level of course PV131 or at least PB130 is required
Course Enrolment Limitations
The course is also offered to the students of the fields other than those the course is directly associated with.
The capacity limit for the course is 25 student(s).
Current registration and enrolment status: enrolled: 0/25, only registered: 0/25, only registered with preference (fields directly associated with the programme): 0/25
fields of study / plans the course is directly associated with
there are 74 fields of study the course is directly associated with, display
Course objectives
The course objective is to strengthen the student's capability of analyzing real-world problems in the field of digital image processing and finding suitable solutions.
Learning outcomes
At the end of the course the student will be able to better solve practical problems from the area of digital image processing.
Syllabus
  • Extension and more profound knowledge of the topics presented in PV131 and PB130 with emphasis on solving a practical project. The projects are in principle of three types:
  • Programming: implementation and testing of a given algorithm (in a chosen programming language)
  • Creative: finding a suitable solution to a given problem
  • Study: testing and comparison of several algorithms/implementations on a given data
Literature
  • Articles published in scientific journals and conference proceedings according to the specification of project leader.
Teaching methods
The student selects a topic from a given list or suggests own topic from the field of digital image processing. (S)he works independently and is supervised by one of the tutors. The results of the work are presented at the end of the semester to other students and tutors.
Assessment methods
To obtain credits, the student must finish the task (process data, write a fully functional computer program), give a presentation and discuss the results at a seminar.
Language of instruction
Czech
Follow-Up Courses
Further Comments
The course is taught annually.
The course is taught: every week.
Teacher's information
http://cbia.fi.muni.cz/
The course is also listed under the following terms Autumn 2004, Autumn 2005, Autumn 2006, Autumn 2007, Autumn 2008, Autumn 2009, Autumn 2010, Autumn 2011, Spring 2013, Autumn 2013, Spring 2014, Autumn 2014, Spring 2015, Autumn 2015, Spring 2016, Autumn 2016, Spring 2017, Autumn 2017, Spring 2018, Autumn 2018, Spring 2019, Autumn 2019, Spring 2020, Autumn 2020, Spring 2021, Autumn 2021.

PV162 Image Processing Project

Faculty of Informatics
Autumn 2021
Extent and Intensity
0/2/0. 2 credit(s) (plus extra credits for completion). Type of Completion: k (colloquium).
Taught online.
Teacher(s)
doc. RNDr. Petr Matula, Ph.D. (lecturer)
doc. RNDr. David Svoboda, Ph.D. (seminar tutor)
doc. RNDr. Pavel Matula, Ph.D. (seminar tutor)
RNDr. Martin Maška, Ph.D. (seminar tutor)
Mgr. Karel Štěpka, Ph.D. (seminar tutor)
prof. RNDr. Michal Kozubek, Ph.D. (seminar tutor)
Guaranteed by
doc. RNDr. Petr Matula, Ph.D.
Department of Visual Computing - Faculty of Informatics
Supplier department: Department of Visual Computing - Faculty of Informatics
Prerequisites
SOUHLAS
Knowledge at the level of course PV131 or at least PB130 is required
Course Enrolment Limitations
The course is also offered to the students of the fields other than those the course is directly associated with.
The capacity limit for the course is 20 student(s).
Current registration and enrolment status: enrolled: 0/20, only registered: 0/20, only registered with preference (fields directly associated with the programme): 0/20
fields of study / plans the course is directly associated with
there are 74 fields of study the course is directly associated with, display
Course objectives
The course objective is to strengthen the student's capability of analyzing real-world problems in the field of digital image processing and finding suitable solutions.
Learning outcomes
At the end of the course, the student will be able to better solve practical problems from the area of digital image processing.
Syllabus
  • Extension and more profound knowledge of the topics presented in PV131 and PB130 with emphasis on solving a practical project. The projects are in principle of three types:
  • Programming: implementation and testing of a given algorithm (in a chosen programming language)
  • Creative: finding a suitable solution to a given problem
  • Study: testing and comparison of several algorithms/implementations on a given data
Literature
  • Articles published in scientific journals and conference proceedings according to the specification of project leader.
Teaching methods
The student selects a topic from a given list or suggests own topic from the field of digital image processing. (S)he works independently and is supervised by one of the tutors. The results of the work are presented at the end of the semester to other students and tutors.
Assessment methods
To obtain credits, the student must finish the task (process data, write a fully functional computer program), give a presentation and discuss the results at a seminar.
Language of instruction
Czech
Follow-Up Courses
Further Comments
The course is taught annually.
The course is taught: every week.
Teacher's information
http://cbia.fi.muni.cz/
The course is also listed under the following terms Autumn 2004, Autumn 2005, Autumn 2006, Autumn 2007, Autumn 2008, Autumn 2009, Autumn 2010, Autumn 2011, Spring 2013, Autumn 2013, Spring 2014, Autumn 2014, Spring 2015, Autumn 2015, Spring 2016, Autumn 2016, Spring 2017, Autumn 2017, Spring 2018, Autumn 2018, Spring 2019, Autumn 2019, Spring 2020, Autumn 2020, Spring 2021, Spring 2022.

PV162 Image Processing Project

Faculty of Informatics
Autumn 2020
Extent and Intensity
0/2/0. 2 credit(s) (plus extra credits for completion). Type of Completion: k (colloquium).
Taught online.
Teacher(s)
doc. RNDr. Petr Matula, Ph.D. (lecturer)
doc. RNDr. David Svoboda, Ph.D. (seminar tutor)
doc. RNDr. Pavel Matula, Ph.D. (seminar tutor)
RNDr. Martin Maška, Ph.D. (seminar tutor)
Mgr. Karel Štěpka, Ph.D. (seminar tutor)
prof. RNDr. Michal Kozubek, Ph.D. (seminar tutor)
Guaranteed by
doc. RNDr. Petr Matula, Ph.D.
Department of Visual Computing - Faculty of Informatics
Supplier department: Department of Visual Computing - Faculty of Informatics
Prerequisites
SOUHLAS
Knowledge at the level of course PV131 or at least PB130 is required
Course Enrolment Limitations
The course is also offered to the students of the fields other than those the course is directly associated with.
The capacity limit for the course is 20 student(s).
Current registration and enrolment status: enrolled: 4/20, only registered: 0/20, only registered with preference (fields directly associated with the programme): 0/20
fields of study / plans the course is directly associated with
there are 74 fields of study the course is directly associated with, display
Course objectives
The course objective is to strengthen the student's capability of analyzing real-world problems in the field of digital image processing and finding suitable solutions.
Learning outcomes
At the end of the course, the student will be able to better solve practical problems from the area of digital image processing.
Syllabus
  • Extension and more profound knowledge of the topics presented in PV131 and PB130 with emphasis on solving a practical project. The projects are in principle of three types:
  • Programming: implementation and testing of a given algorithm (in a chosen programming language)
  • Creative: finding a suitable solution to a given problem
  • Study: testing and comparison of several algorithms/implementations on a given data
Literature
  • Articles published in scientific journals and conference proceedings according to the specification of project leader.
Teaching methods
The student selects a topic from a given list or suggests own topic from the field of digital image processing. (S)he works independently and is supervised by one of the tutors. The results of the work are presented at the end of the semester to other students and tutors.
Assessment methods
To obtain credits, the student must finish the task (process data, write a fully functional computer program), give a presentation and discuss the results at a seminar.
Language of instruction
Czech
Follow-Up Courses
Further Comments
Study Materials
The course is taught annually.
The course is taught: every week.
Teacher's information
http://cbia.fi.muni.cz/
The course is also listed under the following terms Autumn 2004, Autumn 2005, Autumn 2006, Autumn 2007, Autumn 2008, Autumn 2009, Autumn 2010, Autumn 2011, Spring 2013, Autumn 2013, Spring 2014, Autumn 2014, Spring 2015, Autumn 2015, Spring 2016, Autumn 2016, Spring 2017, Autumn 2017, Spring 2018, Autumn 2018, Spring 2019, Autumn 2019, Spring 2020, Spring 2021, Autumn 2021, Spring 2022.

PV162 Image Processing Project

Faculty of Informatics
Spring 2020
Extent and Intensity
0/2. 2 credit(s) (plus extra credits for completion). Type of Completion: k (colloquium).
Teacher(s)
doc. RNDr. Petr Matula, Ph.D. (lecturer)
doc. RNDr. David Svoboda, Ph.D. (seminar tutor)
doc. RNDr. Pavel Matula, Ph.D. (seminar tutor)
Dmitry Sorokin, Ph.D. (seminar tutor)
RNDr. Martin Maška, Ph.D. (seminar tutor)
prof. RNDr. Michal Kozubek, Ph.D. (seminar tutor)
Mgr. Karel Štěpka, Ph.D. (seminar tutor)
RNDr. Roman Stoklasa, Ph.D. (seminar tutor)
Guaranteed by
doc. RNDr. Petr Matula, Ph.D.
Department of Visual Computing - Faculty of Informatics
Supplier department: Department of Visual Computing - Faculty of Informatics
Prerequisites
SOUHLAS
Knowledge at the level of course PV131 or at least PB130 is required
Course Enrolment Limitations
The course is also offered to the students of the fields other than those the course is directly associated with.
The capacity limit for the course is 25 student(s).
Current registration and enrolment status: enrolled: 2/25, only registered: 1/25, only registered with preference (fields directly associated with the programme): 1/25
fields of study / plans the course is directly associated with
there are 74 fields of study the course is directly associated with, display
Course objectives
The course objective is to strengthen the student's capability of analyzing real-world problems in the field of digital image processing and finding suitable solutions.
Learning outcomes
At the end of the course the student will be able to better solve practical problems from the area of digital image processing.
Syllabus
  • Extension and more profound knowledge of the topics presented in PV131 and PB130 with emphasis on solving a practical project. The projects are in principle of three types:
  • Programming: implementation and testing of a given algorithm (in a chosen programming language)
  • Creative: finding a suitable solution to a given problem
  • Study: testing and comparison of several algorithms/implementations on a given data
Literature
  • Articles published in scientific journals and conference proceedings according to the specification of project leader.
Teaching methods
The student selects a topic from a given list or suggests own topic from the field of digital image processing. (S)he works independently and is supervised by one of the tutors. The results of the work are presented at the end of the semester to other students and tutors.
Assessment methods
To obtain credits, the student must finish the task (process data, write a fully functional computer program), give a presentation and discuss the results at a seminar.
Language of instruction
Czech
Follow-Up Courses
Further Comments
Study Materials
The course is taught annually.
The course is taught: every week.
Teacher's information
http://cbia.fi.muni.cz/
The course is also listed under the following terms Autumn 2004, Autumn 2005, Autumn 2006, Autumn 2007, Autumn 2008, Autumn 2009, Autumn 2010, Autumn 2011, Spring 2013, Autumn 2013, Spring 2014, Autumn 2014, Spring 2015, Autumn 2015, Spring 2016, Autumn 2016, Spring 2017, Autumn 2017, Spring 2018, Autumn 2018, Spring 2019, Autumn 2019, Autumn 2020, Spring 2021, Autumn 2021, Spring 2022.

PV162 Image Processing Project

Faculty of Informatics
Autumn 2019
Extent and Intensity
0/2/0. 2 credit(s) (plus extra credits for completion). Type of Completion: k (colloquium).
Teacher(s)
doc. RNDr. Petr Matula, Ph.D. (lecturer)
doc. RNDr. David Svoboda, Ph.D. (seminar tutor)
doc. RNDr. Pavel Matula, Ph.D. (seminar tutor)
RNDr. Martin Maška, Ph.D. (seminar tutor)
Mgr. Karel Štěpka, Ph.D. (seminar tutor)
Ing. Martin Spurný (seminar tutor)
prof. RNDr. Michal Kozubek, Ph.D. (seminar tutor)
Guaranteed by
doc. RNDr. Petr Matula, Ph.D.
Department of Visual Computing - Faculty of Informatics
Supplier department: Department of Visual Computing - Faculty of Informatics
Prerequisites
SOUHLAS
Knowledge at the level of course PV131 or at least PB130 is required
Course Enrolment Limitations
The course is also offered to the students of the fields other than those the course is directly associated with.
The capacity limit for the course is 20 student(s).
Current registration and enrolment status: enrolled: 1/20, only registered: 0/20, only registered with preference (fields directly associated with the programme): 0/20
fields of study / plans the course is directly associated with
there are 74 fields of study the course is directly associated with, display
Course objectives
The course objective is to strengthen the student's capability of analyzing real-world problems in the field of digital image processing and finding suitable solutions.
Learning outcomes
At the end of the course, the student will be able to better solve practical problems from the area of digital image processing.
Syllabus
  • Extension and more profound knowledge of the topics presented in PV131 and PB130 with emphasis on solving a practical project. The projects are in principle of three types:
  • Programming: implementation and testing of a given algorithm (in a chosen programming language)
  • Creative: finding a suitable solution to a given problem
  • Study: testing and comparison of several algorithms/implementations on a given data
Literature
  • Articles published in scientific journals and conference proceedings according to the specification of project leader.
Teaching methods
The student selects a topic from a given list or suggests own topic from the field of digital image processing. (S)he works independently and is supervised by one of the tutors. The results of the work are presented at the end of the semester to other students and tutors.
Assessment methods
To obtain credits, the student must finish the task (process data, write a fully functional computer program), give a presentation and discuss the results at a seminar.
Language of instruction
Czech
Follow-Up Courses
Further Comments
The course is taught annually.
The course is taught: every week.
Teacher's information
http://cbia.fi.muni.cz/
The course is also listed under the following terms Autumn 2004, Autumn 2005, Autumn 2006, Autumn 2007, Autumn 2008, Autumn 2009, Autumn 2010, Autumn 2011, Spring 2013, Autumn 2013, Spring 2014, Autumn 2014, Spring 2015, Autumn 2015, Spring 2016, Autumn 2016, Spring 2017, Autumn 2017, Spring 2018, Autumn 2018, Spring 2019, Spring 2020, Autumn 2020, Spring 2021, Autumn 2021, Spring 2022.

PV162 Image Processing Project

Faculty of Informatics
Spring 2019
Extent and Intensity
0/2/0. 2 credit(s) (plus extra credits for completion). Type of Completion: k (colloquium).
Teacher(s)
doc. RNDr. Petr Matula, Ph.D. (lecturer)
doc. RNDr. David Svoboda, Ph.D. (seminar tutor)
doc. RNDr. Pavel Matula, Ph.D. (seminar tutor)
RNDr. Martin Maška, Ph.D. (seminar tutor)
prof. RNDr. Michal Kozubek, Ph.D. (seminar tutor)
Mgr. Karel Štěpka, Ph.D. (seminar tutor)
Cem Emre Akbas (seminar tutor)
Guaranteed by
doc. RNDr. Petr Matula, Ph.D.
Department of Visual Computing - Faculty of Informatics
Supplier department: Department of Visual Computing - Faculty of Informatics
Prerequisites
SOUHLAS
Knowledge at the level of course PV131 or at least PB130 is required
Course Enrolment Limitations
The course is also offered to the students of the fields other than those the course is directly associated with.
The capacity limit for the course is 25 student(s).
Current registration and enrolment status: enrolled: 1/25, only registered: 0/25, only registered with preference (fields directly associated with the programme): 0/25
fields of study / plans the course is directly associated with
there are 37 fields of study the course is directly associated with, display
Course objectives
The course objective is to strengthen the student's capability of analyzing real-world problems in the field of digital image processing and finding suitable solutions.
Learning outcomes
At the end of the course the student will be able to better solve practical problems from the area of digital image processing.
Syllabus
  • Extension and more profound knowledge of the topics presented in PV131 and PB130 with emphasis on solving a practical project. The projects are in principle of three types:
  • Programming: implementation and testing of a given algorithm (in a chosen programming language)
  • Creative: finding a suitable solution to a given problem
  • Study: testing and comparison of several algorithms/implementations on a given data
Literature
  • Articles published in scientific journals and conference proceedings according to the specification of project leader.
Teaching methods
The student selects a topic from a given list or suggests own topic from the field of digital image processing. (S)he works independently and is supervised by one of the tutors. The results of the work are presented at the end of the semester to other students and tutors.
Assessment methods
To obtain credits, the student must finish the task (process data, write a fully functional computer program), give a presentation and discuss the results at a seminar.
Language of instruction
Czech
Follow-Up Courses
Further Comments
Study Materials
The course is taught annually.
The course is taught: every week.
Teacher's information
http://cbia.fi.muni.cz/
The course is also listed under the following terms Autumn 2004, Autumn 2005, Autumn 2006, Autumn 2007, Autumn 2008, Autumn 2009, Autumn 2010, Autumn 2011, Spring 2013, Autumn 2013, Spring 2014, Autumn 2014, Spring 2015, Autumn 2015, Spring 2016, Autumn 2016, Spring 2017, Autumn 2017, Spring 2018, Autumn 2018, Autumn 2019, Spring 2020, Autumn 2020, Spring 2021, Autumn 2021, Spring 2022.

PV162 Image Processing Project

Faculty of Informatics
Autumn 2018
Extent and Intensity
0/2/0. 2 credit(s) (plus extra credits for completion). Type of Completion: k (colloquium).
Teacher(s)
doc. RNDr. Petr Matula, Ph.D. (lecturer)
doc. RNDr. David Svoboda, Ph.D. (seminar tutor)
doc. RNDr. Pavel Matula, Ph.D. (seminar tutor)
RNDr. Martin Maška, Ph.D. (seminar tutor)
Mgr. Karel Štěpka, Ph.D. (seminar tutor)
Ing. Martin Spurný (seminar tutor)
prof. RNDr. Michal Kozubek, Ph.D. (seminar tutor)
Guaranteed by
doc. RNDr. Petr Matula, Ph.D.
Department of Visual Computing - Faculty of Informatics
Supplier department: Department of Visual Computing - Faculty of Informatics
Prerequisites
SOUHLAS
Knowledge at the level of course PV131 or at least PB130 is required
Course Enrolment Limitations
The course is also offered to the students of the fields other than those the course is directly associated with.
The capacity limit for the course is 20 student(s).
Current registration and enrolment status: enrolled: 1/20, only registered: 0/20, only registered with preference (fields directly associated with the programme): 0/20
fields of study / plans the course is directly associated with
there are 37 fields of study the course is directly associated with, display
Course objectives
The course objective is to strengthen the student's capability of analyzing real-world problems in the field of digital image processing and finding suitable solutions.
Learning outcomes
At the end of the course, the student will be able to better solve practical problems from the area of digital image processing.
Syllabus
  • Extension and more profound knowledge of the topics presented in PV131 and PB130 with emphasis on solving a practical project. The projects are in principle of three types:
  • Programming: implementation and testing of a given algorithm (in a chosen programming language)
  • Creative: finding a suitable solution to a given problem
  • Study: testing and comparison of several algorithms/implementations on a given data
Literature
  • Articles published in scientific journals and conference proceedings according to the specification of project leader.
Teaching methods
The student selects a topic from a given list or suggests own topic from the field of digital image processing. (S)he works independently and is supervised by one of the tutors. The results of the work are presented at the end of the semester to other students and tutors.
Assessment methods
To obtain credits, the student must finish the task (process data, write a fully functional computer program), give a presentation and discuss the results at a seminar.
Language of instruction
Czech
Follow-Up Courses
Further Comments
Study Materials
The course is taught annually.
The course is taught: every week.
Teacher's information
http://cbia.fi.muni.cz/
The course is also listed under the following terms Autumn 2004, Autumn 2005, Autumn 2006, Autumn 2007, Autumn 2008, Autumn 2009, Autumn 2010, Autumn 2011, Spring 2013, Autumn 2013, Spring 2014, Autumn 2014, Spring 2015, Autumn 2015, Spring 2016, Autumn 2016, Spring 2017, Autumn 2017, Spring 2018, Spring 2019, Autumn 2019, Spring 2020, Autumn 2020, Spring 2021, Autumn 2021, Spring 2022.

PV162 Image Processing Project

Faculty of Informatics
Spring 2018
Extent and Intensity
0/2/0. 2 credit(s) (plus extra credits for completion). Type of Completion: k (colloquium).
Teacher(s)
doc. RNDr. Petr Matula, Ph.D. (lecturer)
doc. RNDr. David Svoboda, Ph.D. (seminar tutor)
doc. RNDr. Pavel Matula, Ph.D. (seminar tutor)
RNDr. Martin Maška, Ph.D. (seminar tutor)
prof. RNDr. Michal Kozubek, Ph.D. (seminar tutor)
Mgr. Karel Štěpka, Ph.D. (seminar tutor)
Cem Emre Akbas (seminar tutor)
Guaranteed by
doc. RNDr. Petr Matula, Ph.D.
Department of Visual Computing - Faculty of Informatics
Supplier department: Department of Visual Computing - Faculty of Informatics
Prerequisites
SOUHLAS
Knowledge at the level of course PV131 or at least PB130 is required
Course Enrolment Limitations
The course is also offered to the students of the fields other than those the course is directly associated with.
The capacity limit for the course is 25 student(s).
Current registration and enrolment status: enrolled: 0/25, only registered: 0/25, only registered with preference (fields directly associated with the programme): 0/25
fields of study / plans the course is directly associated with
there are 37 fields of study the course is directly associated with, display
Course objectives
The course objective is to strengthen the student's capability of analyzing real-world problems in the field of digital image processing and finding suitable solutions.
Learning outcomes
At the end of the course the student will be able to better solve practical problems from the area of digital image processing.
Syllabus
  • Extension and deeper knowledge of the topics presented in PV131 and PB130 with emphasis on solving a practical project. The projects are in principle of three types:
  • Programming - implementation and testing of a given algorithm (in a chosen programming language)
  • Creative - finding a suitable solution to a given problem
  • Study - testing and comparison of several algorithms/implementations on a given data
Literature
  • Articles published in scientific journals and conference proceedings according to the specification of project leader.
Teaching methods
The student selects a topic from a given list or suggests own topic from the field of digital image processing. (S)he works independently and is supervised by one of the tutors. The results of the work are presented at the end of the semester to other students and tutors.
Assessment methods
In order to obtain credits, it is necessary to finish the task (process data, write a fully functional computer program), give a presentation and discuss the results at a seminar.
Language of instruction
Czech
Follow-Up Courses
Further Comments
Study Materials
The course is taught annually.
The course is taught: every week.
Teacher's information
http://cbia.fi.muni.cz/
The course is also listed under the following terms Autumn 2004, Autumn 2005, Autumn 2006, Autumn 2007, Autumn 2008, Autumn 2009, Autumn 2010, Autumn 2011, Spring 2013, Autumn 2013, Spring 2014, Autumn 2014, Spring 2015, Autumn 2015, Spring 2016, Autumn 2016, Spring 2017, Autumn 2017, Autumn 2018, Spring 2019, Autumn 2019, Spring 2020, Autumn 2020, Spring 2021, Autumn 2021, Spring 2022.

PV162 Image Processing Project

Faculty of Informatics
Autumn 2017
Extent and Intensity
0/2/0. 2 credit(s) (plus extra credits for completion). Type of Completion: k (colloquium).
Teacher(s)
doc. RNDr. Petr Matula, Ph.D. (lecturer)
doc. RNDr. David Svoboda, Ph.D. (seminar tutor)
doc. RNDr. Pavel Matula, Ph.D. (seminar tutor)
RNDr. Martin Maška, Ph.D. (seminar tutor)
Mgr. Karel Štěpka, Ph.D. (seminar tutor)
Ing. Martin Spurný (seminar tutor)
prof. RNDr. Michal Kozubek, Ph.D. (seminar tutor)
Guaranteed by
doc. RNDr. Petr Matula, Ph.D.
Department of Visual Computing - Faculty of Informatics
Supplier department: Department of Visual Computing - Faculty of Informatics
Prerequisites
SOUHLAS
Knowledge at the level of course PV131 or at least PB130 is required
Course Enrolment Limitations
The course is also offered to the students of the fields other than those the course is directly associated with.
The capacity limit for the course is 20 student(s).
Current registration and enrolment status: enrolled: 0/20, only registered: 0/20, only registered with preference (fields directly associated with the programme): 0/20
fields of study / plans the course is directly associated with
there are 37 fields of study the course is directly associated with, display
Course objectives
The course objective is to strengthen the student's capability of analyzing real-world problems in the field of digital image processing and finding suitable solutions.
Learning outcomes
At the end of the course the student will be able to better solve practical problems from the area of digital image processing.
Syllabus
  • Extension and deeper knowledge of the topics presented in PV131 and PB130 with emphasis on solving a practical project. The projects are in principle of three types:
  • Programming - implementation and testing of a given algorithm (in a chosen programming language)
  • Creative - finding a suitable solution to a given problem
  • Study - testing and comparison of several algorithms/implementations on a given data
Literature
  • Articles published in scientific journals and conference proceedings according to the specification of project leader.
Teaching methods
The student selects a topic from a given list or suggests own topic from the field of digital image processing. (S)he works independently and is supervised by one of the tutors. The results of the work are presented at the end of the semester to other students and tutors.
Assessment methods
In order to obtain credits, it is necessary to finish the task (process data, write a fully functional computer program), give a presentation and discuss the results at a seminar.
Language of instruction
Czech
Follow-Up Courses
Further Comments
Study Materials
The course is taught annually.
The course is taught: every week.
Teacher's information
http://cbia.fi.muni.cz/
The course is also listed under the following terms Autumn 2004, Autumn 2005, Autumn 2006, Autumn 2007, Autumn 2008, Autumn 2009, Autumn 2010, Autumn 2011, Spring 2013, Autumn 2013, Spring 2014, Autumn 2014, Spring 2015, Autumn 2015, Spring 2016, Autumn 2016, Spring 2017, Spring 2018, Autumn 2018, Spring 2019, Autumn 2019, Spring 2020, Autumn 2020, Spring 2021, Autumn 2021, Spring 2022.

PV162 Image Processing Project

Faculty of Informatics
Spring 2017
Extent and Intensity
0/2. 2 credit(s) (plus extra credits for completion). Type of Completion: k (colloquium).
Teacher(s)
doc. RNDr. Petr Matula, Ph.D. (lecturer)
doc. RNDr. David Svoboda, Ph.D. (seminar tutor)
doc. RNDr. Pavel Matula, Ph.D. (seminar tutor)
Dmitry Sorokin, Ph.D. (seminar tutor)
RNDr. Martin Maška, Ph.D. (seminar tutor)
prof. RNDr. Michal Kozubek, Ph.D. (seminar tutor)
Mgr. Karel Štěpka, Ph.D. (seminar tutor)
RNDr. Roman Stoklasa, Ph.D. (seminar tutor)
Guaranteed by
doc. RNDr. Petr Matula, Ph.D.
Department of Visual Computing - Faculty of Informatics
Supplier department: Department of Visual Computing - Faculty of Informatics
Prerequisites
SOUHLAS
Knowledge at the level of course PV131 or at least PB130 is required
Course Enrolment Limitations
The course is also offered to the students of the fields other than those the course is directly associated with.
The capacity limit for the course is 25 student(s).
Current registration and enrolment status: enrolled: 0/25, only registered: 0/25, only registered with preference (fields directly associated with the programme): 0/25
fields of study / plans the course is directly associated with
there are 37 fields of study the course is directly associated with, display
Course objectives
The course objective is to strengthen the student's capability of analyzing real-world problems in the field of digital image processing and finding suitable solutions.
Syllabus
  • Extension and deeper knowledge of the topics presented in PV131 and PB130 with emphasis on solving a practical project. The projects are in principle of three types:
  • Programming - implementation and testing of a given algorithm (in a chosen programming language)
  • Creative - finding a suitable solution to a given problem
  • Study - testing and comparison of several algorithms/implementations on a given data
Literature
  • Articles published in scientific journals and conference proceedings according to the specification of project leader.
Teaching methods
The student selects a topic from a given list or suggests own topic from the field of digital image processing. (S)he works independently and is supervised by one of the tutors. The results of the work are presented at the end of the semester to other students and tutors.
Assessment methods
In order to obtain credits, it is necessary to finish the task (process data, write a fully functional computer program), give a presentation and discuss the results at a seminar.
Language of instruction
Czech
Follow-Up Courses
Further Comments
Study Materials
The course is taught annually.
The course is taught: every week.
Teacher's information
http://cbia.fi.muni.cz/
The course is also listed under the following terms Autumn 2004, Autumn 2005, Autumn 2006, Autumn 2007, Autumn 2008, Autumn 2009, Autumn 2010, Autumn 2011, Spring 2013, Autumn 2013, Spring 2014, Autumn 2014, Spring 2015, Autumn 2015, Spring 2016, Autumn 2016, Autumn 2017, Spring 2018, Autumn 2018, Spring 2019, Autumn 2019, Spring 2020, Autumn 2020, Spring 2021, Autumn 2021, Spring 2022.

PV162 Image Processing Project

Faculty of Informatics
Autumn 2016
Extent and Intensity
0/2/0. 2 credit(s) (plus extra credits for completion). Type of Completion: k (colloquium).
Teacher(s)
doc. RNDr. Petr Matula, Ph.D. (lecturer)
doc. RNDr. David Svoboda, Ph.D. (seminar tutor)
doc. RNDr. Pavel Matula, Ph.D. (seminar tutor)
RNDr. Martin Maška, Ph.D. (seminar tutor)
Mgr. Karel Štěpka, Ph.D. (seminar tutor)
RNDr. Roman Stoklasa, Ph.D. (seminar tutor)
prof. RNDr. Michal Kozubek, Ph.D. (seminar tutor)
Guaranteed by
doc. RNDr. Petr Matula, Ph.D.
Department of Visual Computing - Faculty of Informatics
Supplier department: Department of Visual Computing - Faculty of Informatics
Prerequisites
SOUHLAS
Knowledge at the level of course PV131 or at least PB130 is required
Course Enrolment Limitations
The course is also offered to the students of the fields other than those the course is directly associated with.
The capacity limit for the course is 20 student(s).
Current registration and enrolment status: enrolled: 0/20, only registered: 0/20, only registered with preference (fields directly associated with the programme): 0/20
fields of study / plans the course is directly associated with
there are 37 fields of study the course is directly associated with, display
Course objectives
The course objective is to strengthen the student's capability of analyzing real-world problems in the field of digital image processing and finding suitable solutions.
Syllabus
  • Extension and deeper knowledge of the topics presented in PV131 and PB130 with emphasis on solving a practical project. The projects are in principle of three types:
  • Programming - implementation and testing of a given algorithm (in a chosen programming language)
  • Creative - finding a suitable solution to a given problem
  • Study - testing and comparison of several algorithms/implementations on a given data
Literature
  • Articles published in scientific journals and conference proceedings according to the specification of project leader.
Teaching methods
The student selects a topic from a given list or suggests own topic from the field of digital image processing. (S)he works independently and is supervised by one of the tutors. The results of the work are presented at the end of the semester to other students and tutors.
Assessment methods
In order to obtain credits, it is necessary to finish the task (process data, write a fully functional computer program), give a presentation and discuss the results at a seminar.
Language of instruction
Czech
Follow-Up Courses
Further Comments
Study Materials
The course is taught annually.
The course is taught: every week.
Teacher's information
http://cbia.fi.muni.cz/
The course is also listed under the following terms Autumn 2004, Autumn 2005, Autumn 2006, Autumn 2007, Autumn 2008, Autumn 2009, Autumn 2010, Autumn 2011, Spring 2013, Autumn 2013, Spring 2014, Autumn 2014, Spring 2015, Autumn 2015, Spring 2016, Spring 2017, Autumn 2017, Spring 2018, Autumn 2018, Spring 2019, Autumn 2019, Spring 2020, Autumn 2020, Spring 2021, Autumn 2021, Spring 2022.

PV162 Image Processing Project

Faculty of Informatics
Spring 2016
Extent and Intensity
0/2. 2 credit(s) (plus extra credits for completion). Type of Completion: k (colloquium).
Teacher(s)
doc. RNDr. Petr Matula, Ph.D. (lecturer)
doc. RNDr. David Svoboda, Ph.D. (seminar tutor)
doc. RNDr. Pavel Matula, Ph.D. (seminar tutor)
Dmitry Sorokin, Ph.D. (seminar tutor)
RNDr. Martin Maška, Ph.D. (seminar tutor)
prof. RNDr. Michal Kozubek, Ph.D. (seminar tutor)
Mgr. Karel Štěpka, Ph.D. (seminar tutor)
RNDr. Roman Stoklasa, Ph.D. (seminar tutor)
Guaranteed by
doc. RNDr. Petr Matula, Ph.D.
Department of Visual Computing - Faculty of Informatics
Supplier department: Department of Visual Computing - Faculty of Informatics
Prerequisites
SOUHLAS
Knowledge at the level of course PV131 or at least PB130 is required
Course Enrolment Limitations
The course is also offered to the students of the fields other than those the course is directly associated with.
The capacity limit for the course is 25 student(s).
Current registration and enrolment status: enrolled: 0/25, only registered: 0/25, only registered with preference (fields directly associated with the programme): 0/25
fields of study / plans the course is directly associated with
there are 37 fields of study the course is directly associated with, display
Course objectives
The student will gain a deeper knowledge about a chosen area of digital image processing solved in the Centre for Biomedical Image Analysis and will apply this knowledge during the work on an individual project. This will strengthen the student's capability of analyzing real-world problems in the given field and finding suitable solutions.
Syllabus
  • Extension and deeper knowledge of the topics presented in PV131 and PB130 with emphasis on practical applications.
Literature
  • Articles published in scientific journals and conference proceedings according to the specification of project leader.
Teaching methods
Independent programming activity, usually in C/C++, Matlab, Java, or Python based on a task description and regular consultations with project leader.
Assessment methods
In order to obtain credits, it is necessary to finish the task (process data, write a fully functional computer program), give a presentation and discuss the results at a seminar.
Language of instruction
Czech
Follow-Up Courses
Further Comments
Study Materials
The course is taught annually.
The course is taught: every week.
Teacher's information
http://cbia.fi.muni.cz/
The course is also listed under the following terms Autumn 2004, Autumn 2005, Autumn 2006, Autumn 2007, Autumn 2008, Autumn 2009, Autumn 2010, Autumn 2011, Spring 2013, Autumn 2013, Spring 2014, Autumn 2014, Spring 2015, Autumn 2015, Autumn 2016, Spring 2017, Autumn 2017, Spring 2018, Autumn 2018, Spring 2019, Autumn 2019, Spring 2020, Autumn 2020, Spring 2021, Autumn 2021, Spring 2022.

PV162 Image Processing Project

Faculty of Informatics
Autumn 2015
Extent and Intensity
0/2. 2 credit(s) (plus extra credits for completion). Type of Completion: k (colloquium).
Teacher(s)
doc. RNDr. Petr Matula, Ph.D. (lecturer)
doc. RNDr. David Svoboda, Ph.D. (lecturer)
doc. RNDr. Pavel Matula, Ph.D. (assistant)
RNDr. Martin Maška, Ph.D. (assistant)
Dmitry Sorokin, Ph.D. (assistant)
Mgr. Karel Štěpka, Ph.D. (assistant)
RNDr. Vladimír Ulman, Ph.D. (assistant)
prof. RNDr. Michal Kozubek, Ph.D. (lecturer)
RNDr. Ing. Bc. Tomáš Majtner, Ph.D. (assistant)
RNDr. Roman Stoklasa, Ph.D. (assistant)
Guaranteed by
doc. RNDr. Petr Matula, Ph.D.
Department of Visual Computing - Faculty of Informatics
Supplier department: Department of Visual Computing - Faculty of Informatics
Prerequisites
SOUHLAS
Finished course PV131 or at least PB130 is assumed.
Course Enrolment Limitations
The course is also offered to the students of the fields other than those the course is directly associated with.
The capacity limit for the course is 20 student(s).
Current registration and enrolment status: enrolled: 0/20, only registered: 0/20, only registered with preference (fields directly associated with the programme): 0/20
fields of study / plans the course is directly associated with
there are 37 fields of study the course is directly associated with, display
Course objectives
The student will gain a deeper knowledge about a chosen area of digital image processing solved in the Centre for Biomedical Image Analysis and will apply this knowledge during the work on an individual project. This will strengthen the student's capability of analyzing real-world problems in the given field and finding suitable solutions.
Syllabus
  • Extension and deeper knowledge of the topics presented in PV131 and PB130 with emphasis on practical applications.
Literature
  • Articles published in scientific journals and conference proceedings according to the specification of project leader.
Teaching methods
Independent programming activity, usually in C/C++, Java or Matlab, based on a task description and regular consultations with project leader.
Assessment methods
In order to pass this course, it is necessary to finish the task (process data, write a fully functional computer program), give a presentation and discuss the results at a seminar.
Language of instruction
Czech
Follow-Up Courses
Further Comments
Study Materials
The course is taught annually.
The course is taught: every week.
Teacher's information
http://cbia.fi.muni.cz/
The course is also listed under the following terms Autumn 2004, Autumn 2005, Autumn 2006, Autumn 2007, Autumn 2008, Autumn 2009, Autumn 2010, Autumn 2011, Spring 2013, Autumn 2013, Spring 2014, Autumn 2014, Spring 2015, Spring 2016, Autumn 2016, Spring 2017, Autumn 2017, Spring 2018, Autumn 2018, Spring 2019, Autumn 2019, Spring 2020, Autumn 2020, Spring 2021, Autumn 2021, Spring 2022.

PV162 Image Processing Project

Faculty of Informatics
Spring 2015
Extent and Intensity
0/2. 2 credit(s) (plus extra credits for completion). Type of Completion: z (credit).
Teacher(s)
doc. RNDr. Petr Matula, Ph.D. (lecturer)
doc. RNDr. David Svoboda, Ph.D. (lecturer)
doc. RNDr. Pavel Matula, Ph.D. (seminar tutor)
Dmitry Sorokin, Ph.D. (seminar tutor)
RNDr. Martin Maška, Ph.D. (seminar tutor)
RNDr. Pavel Karas, Ph.D. (seminar tutor)
RNDr. David Novák, Ph.D. (seminar tutor)
Mgr. Karel Štěpka, Ph.D. (seminar tutor)
RNDr. Vladimír Ulman, Ph.D. (seminar tutor)
Guaranteed by
doc. RNDr. Petr Matula, Ph.D.
Department of Visual Computing - Faculty of Informatics
Supplier department: Department of Visual Computing - Faculty of Informatics
Prerequisites
SOUHLAS
Knowledge at the level of course PV131 or at least PB130 is required
Course Enrolment Limitations
The course is also offered to the students of the fields other than those the course is directly associated with.
The capacity limit for the course is 25 student(s).
Current registration and enrolment status: enrolled: 0/25, only registered: 0/25, only registered with preference (fields directly associated with the programme): 0/25
fields of study / plans the course is directly associated with
there are 36 fields of study the course is directly associated with, display
Course objectives
The student will gain a deeper knowledge about a chosen area of digital image processing solved in the Centre for Biomedical Image Analysis and will apply this knowledge during the work on an individual project. This will strengthen the student's capability of analyzing real-world problems in the given field and finding suitable solutions.
Syllabus
  • Extension and deeper knowledge of the topics presented in PV131 and PB130 with emphasis on practical applications.
Literature
  • Articles published in scientific journals and conference proceedings according to the specification of project leader.
Teaching methods
Independent programming activity, usually in C/C++, Matlab, Java, or Python based on a task description and regular consultations with project leader.
Assessment methods
In order to obtain credits, it is necessary to finish the task (process data, write a fully functional computer program) and give a final short presentation on a seminar.
Language of instruction
Czech
Follow-Up Courses
Further Comments
Study Materials
The course is taught annually.
The course is taught: every week.
Teacher's information
http://cbia.fi.muni.cz/
The course is also listed under the following terms Autumn 2004, Autumn 2005, Autumn 2006, Autumn 2007, Autumn 2008, Autumn 2009, Autumn 2010, Autumn 2011, Spring 2013, Autumn 2013, Spring 2014, Autumn 2014, Autumn 2015, Spring 2016, Autumn 2016, Spring 2017, Autumn 2017, Spring 2018, Autumn 2018, Spring 2019, Autumn 2019, Spring 2020, Autumn 2020, Spring 2021, Autumn 2021, Spring 2022.

PV162 Image Processing Project

Faculty of Informatics
Autumn 2014
Extent and Intensity
0/2. 2 credit(s) (plus extra credits for completion). Type of Completion: z (credit).
Teacher(s)
doc. RNDr. Petr Matula, Ph.D. (lecturer)
doc. RNDr. David Svoboda, Ph.D. (lecturer)
doc. RNDr. Pavel Matula, Ph.D. (assistant)
RNDr. Martin Maška, Ph.D. (assistant)
Dmitry Sorokin, Ph.D. (assistant)
RNDr. Pavel Karas, Ph.D. (assistant)
Mgr. Karel Štěpka, Ph.D. (assistant)
RNDr. Vladimír Ulman, Ph.D. (assistant)
RNDr. Ing. Bc. Tomáš Majtner, Ph.D. (assistant)
RNDr. Roman Stoklasa, Ph.D. (assistant)
Guaranteed by
doc. RNDr. Petr Matula, Ph.D.
Department of Visual Computing - Faculty of Informatics
Supplier department: Department of Visual Computing - Faculty of Informatics
Prerequisites
SOUHLAS
Finished course PV131 or at least PB130 is assumed.
Course Enrolment Limitations
The course is also offered to the students of the fields other than those the course is directly associated with.
The capacity limit for the course is 20 student(s).
Current registration and enrolment status: enrolled: 0/20, only registered: 0/20, only registered with preference (fields directly associated with the programme): 0/20
fields of study / plans the course is directly associated with
there are 36 fields of study the course is directly associated with, display
Course objectives
The student will gain a deeper knowledge about a chosen area of digital image processing solved in the Centre for Biomedical Image Analysis and will apply this knowledge during the work on an individual project. This will strengthen the student's capability of analyzing real-world problems in the given field and finding suitable solutions.
Syllabus
  • Extension and deeper knowledge of the topics presented in PV131 and PB130 with emphasis on practical applications.
Literature
  • Articles published in scientific journals and conference proceedings according to the specification of project leader.
Teaching methods
Independent programming activity, usually in C/C++, Java or Matlab, based on a task description and regular consultations with project leader.
Assessment methods
In order to pass this course, it is necessary to finish the task (process data, write a fully functional computer program) and give a final short presentation.
Language of instruction
Czech
Follow-Up Courses
Further Comments
Study Materials
The course is taught annually.
The course is taught: every week.
Teacher's information
http://cbia.fi.muni.cz/
The course is also listed under the following terms Autumn 2004, Autumn 2005, Autumn 2006, Autumn 2007, Autumn 2008, Autumn 2009, Autumn 2010, Autumn 2011, Spring 2013, Autumn 2013, Spring 2014, Spring 2015, Autumn 2015, Spring 2016, Autumn 2016, Spring 2017, Autumn 2017, Spring 2018, Autumn 2018, Spring 2019, Autumn 2019, Spring 2020, Autumn 2020, Spring 2021, Autumn 2021, Spring 2022.

PV162 Image Processing Project

Faculty of Informatics
Spring 2014
Extent and Intensity
0/2. 2 credit(s) (plus extra credits for completion). Type of Completion: z (credit).
Teacher(s)
doc. RNDr. Pavel Matula, Ph.D. (lecturer)
doc. RNDr. David Svoboda, Ph.D. (lecturer)
Dmitry Sorokin, Ph.D. (lecturer)
RNDr. Martin Maška, Ph.D. (lecturer)
doc. RNDr. Petr Matula, Ph.D. (lecturer)
RNDr. Pavel Karas, Ph.D. (assistant)
RNDr. David Novák, Ph.D. (assistant)
Mgr. Karel Štěpka, Ph.D. (assistant)
RNDr. Vladimír Ulman, Ph.D. (assistant)
Guaranteed by
doc. RNDr. Petr Matula, Ph.D.
Department of Visual Computing - Faculty of Informatics
Supplier department: Department of Visual Computing - Faculty of Informatics
Prerequisites
SOUHLAS
Knowledge at the level of course PV131 or at least PB130 is required
Course Enrolment Limitations
The course is also offered to the students of the fields other than those the course is directly associated with.
The capacity limit for the course is 20 student(s).
Current registration and enrolment status: enrolled: 0/20, only registered: 0/20, only registered with preference (fields directly associated with the programme): 0/20
fields of study / plans the course is directly associated with
there are 36 fields of study the course is directly associated with, display
Course objectives
The student will gain a deeper knowledge about a chosen area of digital image processing solved in the Centre for Biomedical Image Analysis and will apply this knowledge during the work on an individual project. This will strengthen the student's capability of analyzing real-world problems in the given field and finding suitable solutions.
Syllabus
  • Extension and deeper knowledge of the topics presented in PV131 with emphasis on practical applications.
Literature
  • Articles published in scientific journals and conference proceedings according to the specification of project leader.
Teaching methods
Independent programming activity, usually in C/C++, Matlab, Java, or Python based on a task description and regular consultations with project leader.
Assessment methods
In order to obtain credits, it is necessary to finish the task (process data, write a fully functional computer program) and give a final short presentation on a seminar.
Language of instruction
Czech
Follow-Up Courses
Further Comments
Study Materials
The course is taught annually.
The course is taught: every week.
Teacher's information
http://cbia.fi.muni.cz/
The course is also listed under the following terms Autumn 2004, Autumn 2005, Autumn 2006, Autumn 2007, Autumn 2008, Autumn 2009, Autumn 2010, Autumn 2011, Spring 2013, Autumn 2013, Autumn 2014, Spring 2015, Autumn 2015, Spring 2016, Autumn 2016, Spring 2017, Autumn 2017, Spring 2018, Autumn 2018, Spring 2019, Autumn 2019, Spring 2020, Autumn 2020, Spring 2021, Autumn 2021, Spring 2022.

PV162 Image Processing Project

Faculty of Informatics
Autumn 2013
Extent and Intensity
0/2. 2 credit(s) (plus extra credits for completion). Type of Completion: z (credit).
Teacher(s)
doc. RNDr. Pavel Matula, Ph.D. (lecturer)
doc. RNDr. David Svoboda, Ph.D. (lecturer)
Dmitry Sorokin, Ph.D. (lecturer)
RNDr. Martin Maška, Ph.D. (lecturer)
doc. RNDr. Petr Matula, Ph.D. (lecturer)
RNDr. Pavel Karas, Ph.D. (lecturer)
Mgr. Karel Štěpka, Ph.D. (lecturer)
RNDr. Vladimír Ulman, Ph.D. (lecturer)
RNDr. Ing. Bc. Tomáš Majtner, Ph.D. (lecturer)
RNDr. Roman Stoklasa, Ph.D. (lecturer)
Guaranteed by
doc. RNDr. Petr Matula, Ph.D.
Department of Visual Computing - Faculty of Informatics
Supplier department: Department of Visual Computing - Faculty of Informatics
Prerequisites
SOUHLAS
Finished or registered course PV131 is assumed.
Course Enrolment Limitations
The course is also offered to the students of the fields other than those the course is directly associated with.
The capacity limit for the course is 20 student(s).
Current registration and enrolment status: enrolled: 0/20, only registered: 0/20, only registered with preference (fields directly associated with the programme): 0/20
fields of study / plans the course is directly associated with
there are 36 fields of study the course is directly associated with, display
Course objectives
The student will gain a deeper knowledge about a chosen area of digital image processing solved in the Centre for Biomedical Image Analysis and will apply this knowledge during the work on an individual project. This will strengthen the student's capability of analyzing real-world problems in the given field and finding suitable solutions.
Syllabus
  • Extension and deeper knowledge of the topics presented in PV131 with emphasis on practical applications.
Literature
  • Articles published in scientific journals and conference proceedings according to the specification of project leader.
Teaching methods
Independent programming activity, usually in C/C++ or Matlab, based on a task description and regular consultations with project leader.
Assessment methods
In order to pass this course, it is necessary to finish the task (process data, write a fully functional computer program) and give a final short presentation.
Language of instruction
Czech
Follow-Up Courses
Further Comments
Study Materials
The course is taught annually.
The course is taught: every week.
Teacher's information
http://cbia.fi.muni.cz/
The course is also listed under the following terms Autumn 2004, Autumn 2005, Autumn 2006, Autumn 2007, Autumn 2008, Autumn 2009, Autumn 2010, Autumn 2011, Spring 2013, Spring 2014, Autumn 2014, Spring 2015, Autumn 2015, Spring 2016, Autumn 2016, Spring 2017, Autumn 2017, Spring 2018, Autumn 2018, Spring 2019, Autumn 2019, Spring 2020, Autumn 2020, Spring 2021, Autumn 2021, Spring 2022.

PV162 Image Processing Project

Faculty of Informatics
Spring 2013
Extent and Intensity
0/2. 2 credit(s) (plus extra credits for completion). Type of Completion: z (credit).
Teacher(s)
doc. RNDr. Pavel Matula, Ph.D. (lecturer)
doc. RNDr. David Svoboda, Ph.D. (lecturer)
Dmitry Sorokin, Ph.D. (lecturer)
RNDr. Martin Maška, Ph.D. (lecturer)
doc. RNDr. Petr Matula, Ph.D. (lecturer)
RNDr. Pavel Karas, Ph.D. (assistant)
Mgr. Karel Štěpka, Ph.D. (assistant)
RNDr. Vladimír Ulman, Ph.D. (assistant)
Guaranteed by
doc. RNDr. Petr Matula, Ph.D.
Department of Visual Computing - Faculty of Informatics
Supplier department: Department of Visual Computing - Faculty of Informatics
Prerequisites
Finished or registered course PV131 is assumed.
Course Enrolment Limitations
The course is also offered to the students of the fields other than those the course is directly associated with.
The capacity limit for the course is 20 student(s).
Current registration and enrolment status: enrolled: 0/20, only registered: 0/20, only registered with preference (fields directly associated with the programme): 0/20
fields of study / plans the course is directly associated with
there are 36 fields of study the course is directly associated with, display
Course objectives
The student will gain a deeper knowledge about a chosen area of digital image processing solved in the Centre for Biomedical Image Analysis and will apply this knowledge during the work on an individual project. This will strengthen the student's capability of analyzing real-world problems in the given field and finding suitable solutions.
Syllabus
  • Extension and deeper knowledge of the topics presented in PV131 with emphasis on practical applications.
Literature
  • Articles published in scientific journals and conference proceedings according to the specification of project leader.
Teaching methods
Independent programming activity, usually in C/C++ or Matlab, based on a task description and regular consultations with project leader.
Assessment methods
In order to obtain credits, it is necessary to finish the task (process data, write a fully functional computer program) and prepare a final short presentation.
Language of instruction
Czech
Follow-Up Courses
Further Comments
Study Materials
The course is taught annually.
The course is taught: every week.
Teacher's information
http://cbia.fi.muni.cz/
The course is also listed under the following terms Autumn 2004, Autumn 2005, Autumn 2006, Autumn 2007, Autumn 2008, Autumn 2009, Autumn 2010, Autumn 2011, Autumn 2013, Spring 2014, Autumn 2014, Spring 2015, Autumn 2015, Spring 2016, Autumn 2016, Spring 2017, Autumn 2017, Spring 2018, Autumn 2018, Spring 2019, Autumn 2019, Spring 2020, Autumn 2020, Spring 2021, Autumn 2021, Spring 2022.

PV162 Image Processing Project

Faculty of Informatics
Autumn 2011
Extent and Intensity
0/2. 2 credit(s) (plus extra credits for completion). Type of Completion: z (credit).
Teacher(s)
doc. RNDr. Pavel Matula, Ph.D. (lecturer)
doc. RNDr. David Svoboda, Ph.D. (lecturer)
Guaranteed by
prof. Ing. Jiří Sochor, CSc.
Department of Visual Computing - Faculty of Informatics
Prerequisites
Finished or registered course PV131 is assumed.
Course Enrolment Limitations
The course is also offered to the students of the fields other than those the course is directly associated with.
The capacity limit for the course is 20 student(s).
Current registration and enrolment status: enrolled: 0/20, only registered: 0/20, only registered with preference (fields directly associated with the programme): 0/20
fields of study / plans the course is directly associated with
there are 41 fields of study the course is directly associated with, display
Course objectives
The student will gain a deeper knowledge about a chosen area of digital image processing solved in the Centre for Biomedical Image Analysis and will apply this knowledge during the work on an individual project. This will strengthen the student's capability of analyzing real-world problems in the given field and finding suitable solutions.
Syllabus
  • Extension and deeper knowledge of the topics presented in PV131 with emphasis on practical applications.
Literature
  • Articles published in scientific journals and conference proceedings according to the specification of project leader.
Teaching methods
Independent programming activity, usually in C/C++ or Matlab, based on a task description and regular consultations with project leader.
Assessment methods
In order to obtain credits, it is necessary to finish the task (process data, write a fully functional computer program) and prepare a final short presentation.
Language of instruction
Czech
Follow-Up Courses
Further Comments
Study Materials
The course is taught annually.
The course is taught: every week.
Teacher's information
http://cbia.fi.muni.cz/
The course is also listed under the following terms Autumn 2004, Autumn 2005, Autumn 2006, Autumn 2007, Autumn 2008, Autumn 2009, Autumn 2010, Spring 2013, Autumn 2013, Spring 2014, Autumn 2014, Spring 2015, Autumn 2015, Spring 2016, Autumn 2016, Spring 2017, Autumn 2017, Spring 2018, Autumn 2018, Spring 2019, Autumn 2019, Spring 2020, Autumn 2020, Spring 2021, Autumn 2021, Spring 2022.

PV162 Image Processing Project

Faculty of Informatics
Autumn 2010
Extent and Intensity
0/2. 2 credit(s) (plus extra credits for completion). Type of Completion: z (credit).
Teacher(s)
prof. RNDr. Michal Kozubek, Ph.D. (lecturer)
doc. RNDr. Pavel Matula, Ph.D. (lecturer)
doc. RNDr. Petr Matula, Ph.D. (lecturer)
doc. RNDr. David Svoboda, Ph.D. (lecturer)
Guaranteed by
prof. Ing. Jiří Sochor, CSc.
Department of Visual Computing - Faculty of Informatics
Contact Person: prof. RNDr. Michal Kozubek, Ph.D.
Prerequisites
Finished or registered course PV131 is assumed.
Course Enrolment Limitations
The course is also offered to the students of the fields other than those the course is directly associated with.
The capacity limit for the course is 20 student(s).
Current registration and enrolment status: enrolled: 0/20, only registered: 0/20, only registered with preference (fields directly associated with the programme): 0/20
fields of study / plans the course is directly associated with
there are 46 fields of study the course is directly associated with, display
Course objectives
The student will gain a deeper knowledge about a chosen area of digital image processing solved in the Centre for Biomedical Image Analysis and will apply this knowledge during the work on an individual project. This will strengthen the student's capability of analyzing real-world problems in the given field and finding suitable solutions.
Syllabus
  • Extension and deeper knowledge of the topics presented in PV131 with emphasis on practical applications.
Literature
  • Articles published in scientific journals and conference proceedings according to the specification of project leader.
Teaching methods
Independent programming activity, usually in C/C++ or Matlab, based on a task description and regular consultations with project leader.
Assessment methods
In order to obtain credits, it is necessary to finish the task (process data, write a fully functional computer program) and prepare a final short presentation.
Language of instruction
Czech
Follow-Up Courses
Further Comments
Study Materials
The course is taught annually.
The course is taught: every week.
Teacher's information
http://cbia.fi.muni.cz/
The course is also listed under the following terms Autumn 2004, Autumn 2005, Autumn 2006, Autumn 2007, Autumn 2008, Autumn 2009, Autumn 2011, Spring 2013, Autumn 2013, Spring 2014, Autumn 2014, Spring 2015, Autumn 2015, Spring 2016, Autumn 2016, Spring 2017, Autumn 2017, Spring 2018, Autumn 2018, Spring 2019, Autumn 2019, Spring 2020, Autumn 2020, Spring 2021, Autumn 2021, Spring 2022.

PV162 Image Processing Project

Faculty of Informatics
Autumn 2009
Extent and Intensity
0/2. 2 credit(s) (plus extra credits for completion). Type of Completion: z (credit).
Teacher(s)
prof. RNDr. Michal Kozubek, Ph.D. (lecturer)
doc. RNDr. Pavel Matula, Ph.D. (lecturer)
doc. RNDr. Petr Matula, Ph.D. (lecturer)
doc. RNDr. David Svoboda, Ph.D. (lecturer)
Guaranteed by
prof. Ing. Jiří Sochor, CSc.
Department of Visual Computing - Faculty of Informatics
Contact Person: prof. RNDr. Michal Kozubek, Ph.D.
Prerequisites
Finished or registered course PV131 is assumed.
Course Enrolment Limitations
The course is also offered to the students of the fields other than those the course is directly associated with.
The capacity limit for the course is 20 student(s).
Current registration and enrolment status: enrolled: 0/20, only registered: 0/20, only registered with preference (fields directly associated with the programme): 0/20
fields of study / plans the course is directly associated with
there are 46 fields of study the course is directly associated with, display
Course objectives
The student will gain a deeper knowledge about a chosen area of digital image processing solved in the Centre for Biomedical Image Analysis and will apply this knowledge during the work on an individual project. This will strengthen the student's capability of analyzing real-world problems in the given field and finding suitable solutions.
Syllabus
  • Extension and deeper knowledge of the topics presented in PV131 with emphasis on practical applications.
Literature
  • Articles published in scientific journals and conference proceedings according to the specification of project leader.
Teaching methods
Independent programming activity, usually in C/C++ or Matlab, based on a task description and regular consultations with project leader.
Assessment methods
In order to obtain credits, it is necessary to finish the task (process data, write a fully functional computer program) and prepare a final short presentation.
Language of instruction
Czech
Follow-Up Courses
Further Comments
Study Materials
The course is taught annually.
The course is taught: every week.
Teacher's information
http://cbia.fi.muni.cz/
The course is also listed under the following terms Autumn 2004, Autumn 2005, Autumn 2006, Autumn 2007, Autumn 2008, Autumn 2010, Autumn 2011, Spring 2013, Autumn 2013, Spring 2014, Autumn 2014, Spring 2015, Autumn 2015, Spring 2016, Autumn 2016, Spring 2017, Autumn 2017, Spring 2018, Autumn 2018, Spring 2019, Autumn 2019, Spring 2020, Autumn 2020, Spring 2021, Autumn 2021, Spring 2022.

PV162 Image Processing Project

Faculty of Informatics
Autumn 2008
Extent and Intensity
0/2. 2 credit(s) (plus extra credits for completion). Type of Completion: z (credit).
Teacher(s)
prof. RNDr. Michal Kozubek, Ph.D. (lecturer)
doc. RNDr. Pavel Matula, Ph.D. (lecturer)
doc. RNDr. Petr Matula, Ph.D. (lecturer)
doc. RNDr. David Svoboda, Ph.D. (lecturer)
Guaranteed by
prof. Ing. Jiří Sochor, CSc.
Department of Visual Computing - Faculty of Informatics
Contact Person: prof. RNDr. Michal Kozubek, Ph.D.
Prerequisites
Finished or registered course PV131 is assumed.
Course Enrolment Limitations
The course is also offered to the students of the fields other than those the course is directly associated with.
The capacity limit for the course is 20 student(s).
Current registration and enrolment status: enrolled: 0/20, only registered: 0/20, only registered with preference (fields directly associated with the programme): 0/20
fields of study / plans the course is directly associated with
there are 39 fields of study the course is directly associated with, display
Course objectives
The aim of the project is to provide students with a deeper knowledge concerning a chosen area of digital image processing and practical checking of this knowledge by working on the project.
Syllabus
  • Extension and deeper knowledge of the topics presented in PV131 with emphasis on practical applications.
Literature
  • Articles published in scientific journals and conference proceedings according to the specification of project leader.
Assessment methods
Practical tasks with emphasis on image analysis and programming in C/C++. It is necessary to finish the task (process data, write a fully functional computer program) and prepare a final short presentation.
Language of instruction
Czech
Follow-Up Courses
Further Comments
Study Materials
The course is taught annually.
The course is taught: every week.
Teacher's information
http://cbia.fi.muni.cz/
The course is also listed under the following terms Autumn 2004, Autumn 2005, Autumn 2006, Autumn 2007, Autumn 2009, Autumn 2010, Autumn 2011, Spring 2013, Autumn 2013, Spring 2014, Autumn 2014, Spring 2015, Autumn 2015, Spring 2016, Autumn 2016, Spring 2017, Autumn 2017, Spring 2018, Autumn 2018, Spring 2019, Autumn 2019, Spring 2020, Autumn 2020, Spring 2021, Autumn 2021, Spring 2022.

PV162 Image Processing Project

Faculty of Informatics
Autumn 2007
Extent and Intensity
0/2. 2 credit(s) (plus extra credits for completion). Type of Completion: z (credit).
Teacher(s)
prof. RNDr. Michal Kozubek, Ph.D. (lecturer)
doc. RNDr. Pavel Matula, Ph.D. (lecturer)
doc. RNDr. Petr Matula, Ph.D. (lecturer)
doc. RNDr. David Svoboda, Ph.D. (lecturer)
Guaranteed by
prof. Ing. Jiří Sochor, CSc.
Department of Visual Computing - Faculty of Informatics
Contact Person: prof. RNDr. Michal Kozubek, Ph.D.
Prerequisites
Finished or registered course PV131 is assumed.
Course Enrolment Limitations
The course is also offered to the students of the fields other than those the course is directly associated with.
The capacity limit for the course is 20 student(s).
Current registration and enrolment status: enrolled: 0/20, only registered: 0/20, only registered with preference (fields directly associated with the programme): 0/20
fields of study / plans the course is directly associated with
there are 39 fields of study the course is directly associated with, display
Course objectives
The aim of the project is to provide students with a deeper knowledge concerning a chosen area of digital image processing and practical checking of this knowledge by working on the project.
Syllabus
  • Extension and deeper knowledge of the topics presented in PV131 with emphasis on practical applications.
Literature
  • Články z odborných časopisů a sborníků konferencí dle specifikace vedoucího projektu.
Assessment methods (in Czech)
Praktické úkoly, zejména analýzy obrazů a programování v C/C++, podmínkou zápočtu je dokončená práce (zpracovaná data, resp. funkční program).
Language of instruction
Czech
Follow-Up Courses
Further Comments
The course is taught annually.
The course is taught: every week.
Teacher's information
http://cbia.fi.muni.cz/
The course is also listed under the following terms Autumn 2004, Autumn 2005, Autumn 2006, Autumn 2008, Autumn 2009, Autumn 2010, Autumn 2011, Spring 2013, Autumn 2013, Spring 2014, Autumn 2014, Spring 2015, Autumn 2015, Spring 2016, Autumn 2016, Spring 2017, Autumn 2017, Spring 2018, Autumn 2018, Spring 2019, Autumn 2019, Spring 2020, Autumn 2020, Spring 2021, Autumn 2021, Spring 2022.

PV162 Image Processing Project

Faculty of Informatics
Autumn 2006
Extent and Intensity
0/2. 2 credit(s) (plus extra credits for completion). Type of Completion: z (credit).
Teacher(s)
prof. RNDr. Michal Kozubek, Ph.D. (lecturer)
doc. RNDr. Pavel Matula, Ph.D. (lecturer)
doc. RNDr. Petr Matula, Ph.D. (lecturer)
doc. RNDr. David Svoboda, Ph.D. (lecturer)
Guaranteed by
prof. Ing. Jiří Sochor, CSc.
Department of Visual Computing - Faculty of Informatics
Contact Person: prof. RNDr. Michal Kozubek, Ph.D.
Timetable
Thu 8:00–9:50 B204
Prerequisites
Finished or registered course PV131 is assumed.
Course Enrolment Limitations
The course is also offered to the students of the fields other than those the course is directly associated with.
The capacity limit for the course is 20 student(s).
Current registration and enrolment status: enrolled: 0/20, only registered: 0/20, only registered with preference (fields directly associated with the programme): 0/20
fields of study / plans the course is directly associated with
there are 17 fields of study the course is directly associated with, display
Course objectives
The aim of the project is to provide students with a deeper knowledge concerning a chosen area of digital image processing and practical checking of this knowledge by working on the project.
Syllabus
  • Extension and deeper knowledge of the topics presented in PV131 with emphasis on practical applications.
Literature
  • Články z odborných časopisů a sborníků konferencí dle specifikace vedoucího projektu.
Assessment methods (in Czech)
Praktické úkoly, zejména analýzy obrazů a programování v C/C++, podmínkou zápočtu je dokončená práce (zpracovaná data, resp. funkční program).
Language of instruction
Czech
Follow-Up Courses
Further Comments
The course is taught annually.
Teacher's information
http://cbia.fi.muni.cz/
The course is also listed under the following terms Autumn 2004, Autumn 2005, Autumn 2007, Autumn 2008, Autumn 2009, Autumn 2010, Autumn 2011, Spring 2013, Autumn 2013, Spring 2014, Autumn 2014, Spring 2015, Autumn 2015, Spring 2016, Autumn 2016, Spring 2017, Autumn 2017, Spring 2018, Autumn 2018, Spring 2019, Autumn 2019, Spring 2020, Autumn 2020, Spring 2021, Autumn 2021, Spring 2022.

PV162 Image Processing Project

Faculty of Informatics
Autumn 2005
Extent and Intensity
0/2. 2 credit(s) (plus extra credits for completion). Type of Completion: z (credit).
Teacher(s)
prof. RNDr. Michal Kozubek, Ph.D. (lecturer)
doc. RNDr. Pavel Matula, Ph.D. (lecturer)
doc. RNDr. Petr Matula, Ph.D. (lecturer)
Guaranteed by
prof. Ing. Jiří Sochor, CSc.
Department of Visual Computing - Faculty of Informatics
Contact Person: prof. RNDr. Michal Kozubek, Ph.D.
Timetable
Thu 8:00–9:50 B204
Prerequisites
Finished or registered course PV131 is assumed.
Course Enrolment Limitations
The course is also offered to the students of the fields other than those the course is directly associated with.
The capacity limit for the course is 20 student(s).
Current registration and enrolment status: enrolled: 0/20, only registered: 0/20, only registered with preference (fields directly associated with the programme): 0/20
fields of study / plans the course is directly associated with
there are 17 fields of study the course is directly associated with, display
Course objectives
The aim of the project is to provide students with a deeper knowledge concerning a chosen area of digital image processing and practical checking of this knowledge by working on the project.
Syllabus
  • Extension and deeper knowledge of the topics presented in PV131 with emphasis on practical applications.
Literature
  • Články z odborných časopisů a sborníků konferencí dle specifikace vedoucího projektu.
Assessment methods (in Czech)
Praktické úkoly, zejména analýzy obrazů a programování v C/C++, podmínkou zápočtu je dokončená práce (zpracovaná data, resp. funkční program).
Language of instruction
Czech
Further Comments
The course is taught annually.
Teacher's information
http://www.fi.muni.cz/lom/
The course is also listed under the following terms Autumn 2004, Autumn 2006, Autumn 2007, Autumn 2008, Autumn 2009, Autumn 2010, Autumn 2011, Spring 2013, Autumn 2013, Spring 2014, Autumn 2014, Spring 2015, Autumn 2015, Spring 2016, Autumn 2016, Spring 2017, Autumn 2017, Spring 2018, Autumn 2018, Spring 2019, Autumn 2019, Spring 2020, Autumn 2020, Spring 2021, Autumn 2021, Spring 2022.

PV162 Image Processing Project

Faculty of Informatics
Autumn 2004
Extent and Intensity
0/2. 2 credit(s) (plus extra credits for completion). Type of Completion: z (credit).
Teacher(s)
prof. RNDr. Michal Kozubek, Ph.D. (lecturer)
doc. RNDr. Pavel Matula, Ph.D. (lecturer)
doc. RNDr. Petr Matula, Ph.D. (lecturer)
Guaranteed by
prof. PhDr. Karel Pala, CSc.
Department of Machine Learning and Data Processing - Faculty of Informatics
Contact Person: prof. RNDr. Michal Kozubek, Ph.D.
Timetable
Wed 10:00–11:50 B411
Prerequisites
Finished or registered course PV131 is assumed.
Course Enrolment Limitations
The course is also offered to the students of the fields other than those the course is directly associated with.
The capacity limit for the course is 20 student(s).
Current registration and enrolment status: enrolled: 0/20, only registered: 0/20, only registered with preference (fields directly associated with the programme): 0/20
fields of study / plans the course is directly associated with
there are 17 fields of study the course is directly associated with, display
Course objectives
The aim of the project is to provide students with a deeper knowledge concerning a chosen area of digital image processing and practical checking of this knowledge by working on the project.
Syllabus
  • Extension and deeper knowledge of the topics presented in PV131 with emphasis on practical applications.
Literature
  • Články z odborných časopisů a sborníků konferencí dle specifikace vedoucího projektu.
Assessment methods (in Czech)
Praktické úkoly, zejména analýzy obrazů a programování v C/C++, podmínkou zápočtu je dokončená práce (zpracovaná data, resp. funkční program).
Language of instruction
Czech
Further Comments
The course is taught annually.
Teacher's information
http://www.fi.muni.cz/lom/
The course is also listed under the following terms Autumn 2005, Autumn 2006, Autumn 2007, Autumn 2008, Autumn 2009, Autumn 2010, Autumn 2011, Spring 2013, Autumn 2013, Spring 2014, Autumn 2014, Spring 2015, Autumn 2015, Spring 2016, Autumn 2016, Spring 2017, Autumn 2017, Spring 2018, Autumn 2018, Spring 2019, Autumn 2019, Spring 2020, Autumn 2020, Spring 2021, Autumn 2021, Spring 2022.

PV162 Image Processing Project

Faculty of Informatics
Autumn 2012

The course is not taught in Autumn 2012

Extent and Intensity
0/2. 2 credit(s) (plus extra credits for completion). Type of Completion: z (credit).
Teacher(s)
doc. RNDr. Pavel Matula, Ph.D. (lecturer)
doc. RNDr. David Svoboda, Ph.D. (lecturer)
Guaranteed by
prof. Ing. Jiří Sochor, CSc.
Department of Visual Computing - Faculty of Informatics
Supplier department: Department of Visual Computing - Faculty of Informatics
Prerequisites
Finished or registered course PV131 is assumed.
Course Enrolment Limitations
The course is also offered to the students of the fields other than those the course is directly associated with.
The capacity limit for the course is 20 student(s).
Current registration and enrolment status: enrolled: 0/20, only registered: 0/20, only registered with preference (fields directly associated with the programme): 0/20
fields of study / plans the course is directly associated with
there are 36 fields of study the course is directly associated with, display
Course objectives
The student will gain a deeper knowledge about a chosen area of digital image processing solved in the Centre for Biomedical Image Analysis and will apply this knowledge during the work on an individual project. This will strengthen the student's capability of analyzing real-world problems in the given field and finding suitable solutions.
Syllabus
  • Extension and deeper knowledge of the topics presented in PV131 with emphasis on practical applications.
Literature
  • Articles published in scientific journals and conference proceedings according to the specification of project leader.
Teaching methods
Independent programming activity, usually in C/C++ or Matlab, based on a task description and regular consultations with project leader.
Assessment methods
In order to obtain credits, it is necessary to finish the task (process data, write a fully functional computer program) and prepare a final short presentation.
Language of instruction
Czech
Follow-Up Courses
Further Comments
The course is taught annually.
The course is taught: every week.
Teacher's information
http://cbia.fi.muni.cz/
The course is also listed under the following terms Autumn 2004, Autumn 2005, Autumn 2006, Autumn 2007, Autumn 2008, Autumn 2009, Autumn 2010, Autumn 2011, Spring 2013, Autumn 2013, Spring 2014, Autumn 2014, Spring 2015, Autumn 2015, Spring 2016, Autumn 2016, Spring 2017, Autumn 2017, Spring 2018, Autumn 2018, Spring 2019, Autumn 2019, Spring 2020, Autumn 2020, Spring 2021, Autumn 2021, Spring 2022.
  • Enrolment Statistics (recent)