Titlebook: Computer Vision – ECCV 2016; 14th European Confer Bastian Leibe,Jiri Matas,Max Welling Conference proceedings 2016 Springer International P

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Peter Bleses,Martin Seeleib-Kaiserrnels on learned representations is limited. In this work, we explore and employ the relationship between shape of kernels which define receptive fields (RFs) in CNNs for learning of feature representations and image classification. For this purpose, we present a feature visualization method for vis

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Bastian Leibe,Jiri Matas,Max WellingIncludes supplementary material:

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Lecture Notes in Computer Sciencehttp://image.papertrans.cn/c/image/234175.jpg

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Design of Kernels in Convolutional Neural Networks for Image Classificationed an outstanding performance in the classification task, comparing to a base CNN model that introduces more parameters and computational time, using the ILSVRC-2012 dataset?[.]. Additionally, we examined the region of interest (ROI) of different models in the classification task and analyzed the ro