Introduction to Convolutional Neural Networks
نویسنده
چکیده
6 The convolution layer 11 6.1 What is convolution? . . . . . . . . . . . . . . . . . . . . . . . . . 11 6.2 Why to convolve? . . . . . . . . . . . . . . . . . . . . . . . . . . . 13 6.3 Convolution as matrix product . . . . . . . . . . . . . . . . . . . 15 6.4 The Kronecker product . . . . . . . . . . . . . . . . . . . . . . . 17 6.5 Backward propagation: update the parameters . . . . . . . . . . 17 6.6 Even higher dimensional indicator matrices . . . . . . . . . . . . 19 6.7 Backward propagation: prepare supervision signal for the previous layer . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 20 6.8 Fully connected layer as a convolution layer . . . . . . . . . . . . 22
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