Question
Given a Convolution Layer with 8 filters, a filter size of 6, a stride of 2, and a padding of 1. For an input feature map
Given a Convolution Layer with 8 filters, a filter size of 6, a stride of 2, and a padding of 1. For an input feature map of 32 x 32 x 32, what is the output dimensionality after applying the Convolution Layer to the input?
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Koala Tutor
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The output dimensionality of a convolution layer can be calculated using the formula:
O = ((W - K + 2P) / S) + 1
where:
O is the output height/length
W is the input height/length
K is the filter size
P is the padding
S is the stride
So, for the given problem:
O = ((32 - 6 + 2*1) / 2) + 1 = 15
Since the convolution is applied to a 3D input, the output will also be 3D. The number of filters determines the depth of the output, so the output dimensionality will be 15 x 15 x 8.
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