The use of deep learning with Deeplearning4j on the case of facial recognition

V magistrskem delu smo se dotaknili področja globokega učenja, spoznali smo pristope in arhitekture algoritmov globokega učenja ter jih kategorizirali v tri skupine. V nadaljevanju smo podrobneje analizirali knjižnico Deeplearning4j, predstavili osnovne funkcionalnosti ter raziskali njene možnosti za uporabo na področju globokega učenja. V praktičnem delu smo uporabo globokega učenja s knjižnico Deeplearning4j aplicirali na primeru prepoznave obrazov. Implementirali smo dve različici konvolucijskih nevronskih mrež ter dva načina učenja – lokalno ter porazdeljeno učenje.In the master’s thesis, we briefly introduced the area of deep learning. We explored and described the approaches and architectures of deep learning algorithms and categorize them into three groups. In the following, we analyzed Deeplearning4j library, presented main features and studied possibilities of its use in the field of deep learning. In the empirical part, the use of deep learning with Deeplearning4j was applied on the case of facial recognition. We implemented two different versions of convolutional neural networks and two types of learning – local and distributed learning