Cascaded Subpatch Networks for Effective CNNs

IEEE Transactions on Neural Networks and Learning Systems
Xiaoheng JiangXuelong Li

Abstract

Conventional convolutional neural networks use either a linear or a nonlinear filter to extract features from an image patch (region) of spatial size (typically, is small and is equal to , e.g., is 5 or 7). Generally, the size of the filter is equal to the size of the input patch. We argue that the representational ability of equal-size strategy is not strong enough. To overcome the drawback, we propose to use subpatch filter whose spatial size is smaller than . The proposed subpatch filter consists of two subsequent filters. The first one is a linear filter of spatial size and is aimed at extracting features from spatial domain. The second one is of spatial size and is used for strengthening the connection between different input feature channels and for reducing the number of parameters. The subpatch filter convolves with the input patch and the resulting network is called a subpatch network. Taking the output of one subpatch network as input, we further repeat constructing subpatch networks until the output contains only one neuron in spatial domain. These subpatch networks form a new network called the cascaded subpatch network (CSNet). The feature layer generated by CSNet is called the csconv layer. For the whole input ima...Continue Reading

References

Jun 22, 2013·IEEE Transactions on Pattern Analysis and Machine Intelligence·Yoshua BengioPascal Vincent
Nov 25, 2014·IEEE Transactions on Neural Networks and Learning Systems·Yanwei PangYuan Yuan
Nov 25, 2014·IEEE Transactions on Neural Networks and Learning Systems·Ling ShaoXuelong Li
Jan 22, 2015·IEEE Transactions on Neural Networks and Learning Systems·Chih-Hung Chang
May 27, 2015·IEEE Transactions on Image Processing : a Publication of the IEEE Signal Processing Society·Zhong JiXuelong Li
Sep 5, 2015·IEEE Transactions on Neural Networks and Learning Systems·Maoguo GongLinzhi Su
Jan 8, 2016·IEEE Transactions on Cybernetics·Yanwei PangXuelong Li
Mar 10, 2016·IEEE Transactions on Pattern Analysis and Machine Intelligence·Di WuJean-Marc Odobez
Jul 9, 2016·IEEE Transactions on Neural Networks and Learning Systems·Tohru Nitta

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