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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?

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)
Computer Networking: A Top-Down Approach (7th Edition)
7th Edition
ISBN:9780133594140
Author:James Kurose, Keith Ross
Publisher:James Kurose, Keith Ross
Chapter1: Computer Networks And The Internet
Section: Chapter Questions
Problem R1RQ: What is the difference between a host and an end system? List several different types of end...
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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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