WebSep 4, 2024 · Padding basically extends the area of an image in which a convolutional neural network processes. The kernel/filter which moves across the image scans each pixel and converts the image into a smaller image. WebAbout zero padding, it is usually done in almost all CNNs if you use the same convolution which means the height and width of the output activation maps should be equal to the size of their input counterparts. Zero padding is usually done when you want to extract features from inputs with conv layers.

Can someone explain to me what reflection padding does? : learnmachi…

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