神经网络卷积层 要回计算output的维度 input 28 卷积是3x3 则output是26 但是channel是卷积核的数量

 

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model = Sequential() model.add(Conv2D(32, kernel_size=(3, 3),                  activation='relu',                  input_shape=input_shape)) model.add(Conv2D(64, (3, 3), activation='relu')) model.add(MaxPooling2D(pool_size=(2, 2))) model.add(Dropout(0.25)) model.add(Flatten()) model.add(Dense(128, activation='relu')) model.add(Dropout(0.5)) model.add(Dense(num_classes, activation='softmax'))