Thesis Details
Rozpoznávání emocí pomocí konvolučních neuronových sítí
Convolutional neural networks are used for various tasks, but foremost in machine learning, in whichthey excel. This work is going to introduce some existing frameworks, other algorithms forrecognition and then we describe the training dataset creation and the model for emotion recognitiontraining process. Mentioned model has accuracy of 60%. It is used for emotion statistics retrievalfrom movie trailers. Model for genre recognition is created from those statistics and then finally usedin our application for genre recognition of the input trailer, with best accuracy of 47%.
Convolutional neural networks, Facial recognition, Emotion recognition, Movie genre recognition,Caffe framework, CK, AMFED, KDEF, SFEW, Brazilian FEI, K-nearest neigbours, OpenCV.
Drahanský Martin, prof. Ing., Dipl.-Ing., Ph.D. (DITS FIT BUT), člen
Chudý Peter, doc. Ing., Ph.D. MBA (DCGM FIT BUT), člen
Očenášek Pavel, Mgr. Ing., Ph.D. (DIFS FIT BUT), člen
Strnadel Josef, Ing., Ph.D. (DCSY FIT BUT), člen
@bachelorsthesis{FITBT18304, author = "Jan Jile\v{c}ek", type = "Bachelor's thesis", title = "Rozpozn\'{a}v\'{a}n\'{i} emoc\'{i} pomoc\'{i} konvolu\v{c}n\'{i}ch neuronov\'{y}ch s\'{i}t\'{i}", school = "Brno University of Technology, Faculty of Information Technology", year = 2016, location = "Brno, CZ", language = "czech", url = "https://www.fit.vut.cz/study/thesis/18304/" }