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CNNdaima-tuxiangshibie
- 深度学习中的CNN方法,层数由原先的五层增加到七层,使用最新的RELU激活函数代替原先的sigm函数,能运行-CNN depth learning method, the number of layers the original five to seven, with the latest RELU activation function replaces sigm function, you can run it
CNN
- 构建卷积神经网络,包括卷积层,池化层,RELU(Construction of convolution neural network)
Relu1-TensorFlow
- TensorFlow实现relu前馈神经网络(relu BPNN,using TensorFlow)
Conv_neural_net_NumPy
- 用numpy实现卷积神经网络的卷积、池化、ReLU操作。(numpy,Relu,pooling,conv)