Viewing a response to: @cristi/neural-networks-and-tensorflow-deep-learning-series-part-14
I think I missed the last part (part13), but I remember padding. If I remember correctly the output volume keeps on getting smaller for each application of convolution layer. Larger the size of the stride more volume would be lost at the edges. I think the idea of padding was to start with more volume so we end up retaining most of the original input information.
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