Parça Tabanlı Eǧitimin Evrişimli Yapay Sinir Aǧları ile Nesne Konumlandırma Üzerindeki Etkisi
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Orhan, Semih
Bastanlar, Yalin
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Green Open Access
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Abstract
In recent years, Convolutional Neural Networks (CNNs) have shown great performance not only in image classification and image recognition tasks but also several tasks of computer vision. A lot of models which have different number of layers and depths, have been proposed. In this work, locations of leopards are tried to be identified by deep neural networks. To accomplish this task, two different methods are applied. First of them is training neural network using with entire images, second of them is training neural networks using with image patches which are cropped from full size of images. Patch training model has shown better performance than full size of image trained model.
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Keywords
Deep Neural Networks, Convolutional Neural Networks, Object Recognition, Object Localization
Fields of Science
0202 electrical engineering, electronic engineering, information engineering, 02 engineering and technology
Citation
Orhan, S, and Baştanlar, Y. (2017, May 15-18). Parça tabanlı eğitimin evrişimli yapay sinir ağları ile nesne konumlandırma üzerindeki etkisi. Paper presented at the 25th Signal Processing and Communications Applications Conference. doi:10.1109/SIU.2017.7960201
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