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neural-networkdeep-learningartificial-intelligenceconv-neural-networkconvolution
Sakhri Houssem
Sakhri Houssem

Reputation: 1063

How we calculate the Depth of Convolution Output?

How we get Feature maps number in the Conv output (Depth H)

I think that H = D * number of filters !!

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Upvotes: 1

Views: 1997

Answers (1)

myrtlecat
myrtlecat

Reputation: 2276

H can be chosen freely. It does not depend on any of the other parameters.

Each of the H "feature maps" will be produced by a different k x k x D kernel. This is often described as a single 4D kernel with shape H x k x k x D.

In the source text it says the same thing, but perhaps more clearly:

The input is of size N x N x D and is convolved with H kernels, each of size k x k x D separately. Convolution of an input with one kernel produces one output feature, and with H kernels independently produces H features.

The terminology can be confusing at first, as there are multiple terms used for the same thing. H could be called the number of kernels, or number of filters, or number of output features or the number of filter maps.

Upvotes: 3

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