Slide 17
Slide 17 text
const model = tf.sequential();
model.add(tf.layers.conv2d({
inputShape: [IMAGE_WIDTH, IMAGE_HEIGHT, IMAGE_CHANNELS],
kernelSize: 5, filters: 8, strides: 1,
activation: 'relu',
kernelInitializer: 'varianceScaling'
}));
model.add(tf.layers.maxPooling2d({poolSize: [2, 2], strides: [2, 2]}));
...
model.add(tf.layers.flatten());
model.add(tf.layers.dense({ units: NUM_CLASSES, activation: 'softmax' }));
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