Created
October 26, 2018 05:02
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Simple image classification architecture
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model = Sequential() | |
model.add(Conv2D(32, (3, 3), input_shape=input_shape)) | |
model.add(Activation('relu')) | |
model.add(MaxPooling2D(pool_size=(2, 2))) | |
model.add(Conv2D(32, (3, 3))) | |
model.add(Activation('relu')) | |
model.add(MaxPooling2D(pool_size=(2, 2))) | |
model.add(Conv2D(64, (3, 3))) | |
model.add(Activation('relu')) | |
model.add(MaxPooling2D(pool_size=(2, 2))) | |
model.add(Flatten()) | |
model.add(Dense(64)) | |
model.add(Activation('relu')) | |
model.add(Dropout(0.5)) | |
model.add(Dense(1)) | |
model.add(Activation('sigmoid')) |
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