CUNet: A Compact Unsupervised Network for Image Classification

6 Jul 2016Le DongLing HeGaipeng KongQianni ZhangXiaochun CaoEbroul Izquierdo

In this paper, we propose a compact network called CUNet (compact unsupervised network) to counter the image classification challenge. Different from the traditional convolutional neural networks learning filters by the time-consuming stochastic gradient descent, CUNet learns the filter bank from diverse image patches with the simple K-means, which significantly avoids the requirement of scarce labeled training images, reduces the training consumption, and maintains the high discriminative ability... (read more)

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