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Although deep learning has achieved good performances in many pattern recognition tasks, the over-fitting problem is still a serious issue for training deep networks containing large sets of parameters with limited labeled data. In this work, Binarized Auto-encoders (BAEs) and Stacked Binarized Auto-encoders (Stacked BAEs) are proposed to learn a kind of domain knowledge from a large-scale unlabeled...
In this paper, a general framework for 3D convolutional neural networks is proposed. In this framework, five kinds of layers including convolutional layer, max-pooling layer, dropout layer, Gabor layer and optical flow layer are defined. General rules of designing 3D convolutional neural networks are discussed. Four specific networks are designed for facial expression recognition. Decisions of the...
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