Q1) Convolution Neural Network (CNN) a) Explain the concepts of "local connectivity" and "parameter sharing". b) What is the shape of the activation map when applying 6 filters of shape 5x5x3 on input image of shape 28x28x3? c) What is the number of the parameters in case we have an input volume of shape 32x32x3 and we apply 10 filters of shape 5x5x3 with stride of 1 and pad of 2?

Computer Networking: A Top-Down Approach (7th Edition)
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Author:James Kurose, Keith Ross
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Q1) Convolution Neural Network (CNN)
a) Explain the concepts of "local connectivity" and "parameter
sharing".
b) What is the shape of the activation map when applying 6
filters of shape 5x5x3 on input image of shape 28x28x3?
c) What is the number of the parameters in case we have an
input volume of shape 32x32x3 and we apply 10 filters of
shape 5x5x3 with stride of 1 and pad of 2?
Transcribed Image Text:Q1) Convolution Neural Network (CNN) a) Explain the concepts of "local connectivity" and "parameter sharing". b) What is the shape of the activation map when applying 6 filters of shape 5x5x3 on input image of shape 28x28x3? c) What is the number of the parameters in case we have an input volume of shape 32x32x3 and we apply 10 filters of shape 5x5x3 with stride of 1 and pad of 2?
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