AlexNet 模型构建 - Python 代码实现

class AlexNet: @staticmethod def build(width, height, depth, classes, reg='Hone'): model = Sequential() input_shape = (height, width, depth) model.add(Conv2D(96, (11, 11), input_shape=input_shape, strides=4, activation='relu')) model.add(MaxPooling2D(pool_size=(3, 3), strides=2)) model.add(ZeroPadding2D(padding=(2, 2))) model.add(Conv2D(256, (5, 5), activation='relu')) model.add(MaxPooling2D(pool_size=(3, 3), strides=2)) model.add(ZeroPadding2D(padding=(1, 1))) model.add(Conv2D(384, (3, 3), activation='relu')) model.add(ZeroPadding2D(padding=(1, 1))) model.add(Conv2D(384, (3, 3), activation='relu')) model.add(ZeroPadding2D(padding=(1, 1))) model.add(Conv2D(256, (3, 3), activation='relu')) model.add(MaxPooling2D(pool_size=(3, 3), strides=2)) model.add(Flatten()) model.add(Dense(4096, activation='relu')) model.add(Dropout(0.5)) model.add(Dense(4096, activation='relu')) model.add(Dropout(0.5)) model.add(Dense(classes, activation='sigmoid')) return model