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What’s the difference between valid and same padding in a CNN(deep learning)?

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This question has more chances of being a follow-up question to the previous one. Or if you have explained how you used CNNs in a computer vision task, the interviewer might ask this question along with the details of the padding parameters.

  • Valid Padding: When we do not use any padding. The resultant matrix after convolution will have dimensions (n – f + 1) X (n – f + 1)
  • Same padding: Adding padded elements all around the edges such that the output matrix will have the same dimensions as that of the input matrix
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