FI:PV253 Seminar of DISA Laboratory - Course Information
PV253 Seminar of DISA LaboratoryFaculty of Informatics
- Extent and Intensity
- 0/2. 2 credit(s) (plus extra credits for completion). Type of Completion: k (colloquium).
- prof. Ing. Pavel Zezula, CSc. (lecturer)
RNDr. Jan Sedmidubský, Ph.D. (assistant)
- Guaranteed by
- prof. Ing. Pavel Zezula, CSc.
Department of Machine Learning and Data Processing - Faculty of Informatics
Supplier department: Department of Machine Learning and Data Processing - Faculty of Informatics
- Tue 10:00–11:50 A218
- Students should be interested in cooperation on research projects conducted by the laboratory. The knowledge of English is necessary to study original research papers. Basic experience with programming and data management system implementations is an advantage.
- Course Enrolment Limitations
- The course is also offered to the students of the fields other than those the course is directly associated with.
- Fields of study the course is directly associated with
- there are 82 fields of study the course is directly associated with, display
- Course objectives
- The course objective is a presentation of the state-of-the-art knowledge in research areas of the laboratory. A special emphasis is put on presentations of innovative ideas and proposals by researchers involved in current projects of DISA. The seminar is a source of new knowledge for students and other laboratory members and at the same time it forms a feedback for lecturers (prevalently project researchers). Short student presentations working on bachelor or master theses are also part of the course activities.
- Learning outcomes
- Student will improve their presentation skills, and will undesrtand selected research results in the domain of the laboratory.
- The selection of presentations is based on research interests of ongoing projects. At the moment, the topics include:
- Similarity searching and filtering in multimedia data (mainly images and video);
- Searching for sub-images;
- Searching in large collections of biometric data;
- Similarity models of dynamic biometric characteristics (mainly human movements);
- Multimodal interpretation of multimedia data;
- Findability of multimedia data;
- Scalability for knowledge extraction and searching, etc.
- Teaching methods
- The seminar consists of presentations and discussions on the state-of-the-art knowledge in topics of interest of the laboratory. The presentations are delivered by both the students and researchers. The specific topics of interest are determined during the first two weeks of each term.
- Assessment methods
- Regular attendance of the seminar is an assumption. The condition for classification is also an active participation, which can be a software project assignment and/or a presentation on an approved topic.
- Language of instruction
- Follow-Up Courses
- Further Comments
- Study Materials
The course is taught each semester.
- Teacher's information