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@inproceedings{1489696, author = {Miklášová, Kristína and Lomič, Ondřej and Císar, Lukáš and Popelínský, Lubomír and Krejčířová, Veronika}, address = {Brno}, booktitle = {DATA A ZNALOSTI & WIKT 2018, sborník konference}, editor = {Jaroslav Zendulka, Mária Bieliková, Radek Burget, Zbyněk Křivka}, keywords = {Autoencoders · Local Outlier Factor (LOF) · z-score · anomalies · PascalVOC image dataset · feature extraction}, howpublished = {elektronická verze "online"}, language = {eng}, location = {Brno}, isbn = {978-80-214-5679-2}, pages = {215-220}, publisher = {Vysoké učení technické v Brně}, title = {Autoencoders vs. others for anomaly detection}, year = {2018} }
TY - JOUR ID - 1489696 AU - Miklášová, Kristína - Lomič, Ondřej - Císar, Lukáš - Popelínský, Lubomír - Krejčířová, Veronika PY - 2018 TI - Autoencoders vs. others for anomaly detection PB - Vysoké učení technické v Brně CY - Brno SN - 9788021456792 KW - Autoencoders · Local Outlier Factor (LOF) · z-score · anomalies · PascalVOC image dataset · feature extraction N2 - The paper deals with a task of finding anomalies in the set of pictures using autoencoders and comparison of results with other methods searching for outliers, namely LOF and z-score. Outliers found by these methods are compared to outliers found by project team members. Process consists of preprocessing of pictures using pretrained deep neural nets (one at a time), reducing dimension using PCA, normalization of features and applying methods on pictures, either on a whole set or subsets divided by classes (dividing the pictures to groups by objects of interest that can be found in them). Output of methods with different attribute settings was compared to outliers found by team members using confusion matrix and F1-score. The results were not very positive, no significant relationships were found between anomalies found by team members and by anomalies found by individual methods. Possible reasons for this are discussed. ER -
MIKLÁŠOVÁ, Kristína, Ondřej LOMIČ, Lukáš CÍSAR, Lubomír POPELÍNSKÝ a Veronika KREJČÍŘOVÁ. Autoencoders vs. others for anomaly detection. Online. In Jaroslav Zendulka, Mária Bieliková, Radek Burget, Zbyněk Křivka. \textit{DATA A ZNALOSTI \&{} WIKT 2018, sborník konference}. Brno: Vysoké učení technické v Brně, 2018, s.~215-220. ISBN~978-80-214-5679-2.
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