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Assume that an input RGB image below is entering a Convolutional Neural Network: 3 2 2 80 3 5 3 7 3 1 1 5 72 3 7 0 3 5 1 0 2 3 2 11 5 2 3 4 4 6 0 We use the following vertical edge filter to convolve with the image. 2 7 2 1 0 4 2 7 0 4 2 5 7 2 1 1 8 4 7 2 3 3 7 1 0 5 1 1 0 -1 1 0 -1 1 0 -1 If the padding size is 3 and the stride is also 3. The size of the output will be nxn where n is 4 |0 3 0 1 0 -1 0 -1 -1 2 3 5 3 2 7 6 1 1 1 1 0 4 4 7 2 5 6 1 2 5 4 1 8 2 0 0 -1 0 -1 -1 6 4 3 1 4 7 2 8 3 3 5 1 0 7 3 2 1 1 2 6 3 4

Assume that an input RGB image below is entering a Convolutional Neural Network: 3 2 2 80 3 5 3 7 3 1 1 5 72 3 7 0 3 5 1 0 2 3 2 11 5 2 3 4 4 6 0 We use the following vertical edge filter to convolve with the image. 2 7 2 1 0 4 2 7 0 4 2 5 7 2 1 1 8 4 7 2 3 3 7 1 0 5 1 1 0 -1 1 0 -1 1 0 -1 If the padding size is 3 and the stride is also 3. The size of the output will be nxn where n is 4 |0 3 0 1 0 -1 0 -1 -1 2 3 5 3 2 7 6 1 1 1 1 0 4 4 7 2 5 6 1 2 5 4 1 8 2 0 0 -1 0 -1 -1 6 4 3 1 4 7 2 8 3 3 5 1 0 7 3 2 1 1 2 6 3 4

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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Assume that an input RGB image below is entering a Convolutional Neural Network: 3 2 2 4 6 1 8 7 7 3 0 1 0 3 3 5 3 1 1 5 2 7 0 3 5 1 2 3 2 5 2 3 We use the following vertical edge filter to convolve with the image. 2 7 0 4 2 1 0 4 0 7 1 0 -1 1 0 -1 1 0 -1 4 2 5 2 1 1 8 4 7 2 3 3 2 7 05 7 1 4 3 0 1 If the padding size is 3 and the stride is also 3. The size of the output will be nxn where n is 2 3 1 0 -1 1 0 -1 1 0 -1 5 3 2 7 6 1 1 0 1 0 1 0 0 4 4 7 2 8 5 2 6 1 5 4 -1 -1 -1 6 4 1 3 4 2 2 1 5 3 3 | 1 7 0 8 1 2 3 7 3 2 1 6 4
Transcribed Image Text:Assume that an input RGB image below is entering a Convolutional Neural Network: 3 2 2 4 6 1 8 7 7 3 0 1 0 3 3 5 3 1 1 5 2 7 0 3 5 1 2 3 2 5 2 3 We use the following vertical edge filter to convolve with the image. 2 7 0 4 2 1 0 4 0 7 1 0 -1 1 0 -1 1 0 -1 4 2 5 2 1 1 8 4 7 2 3 3 2 7 05 7 1 4 3 0 1 If the padding size is 3 and the stride is also 3. The size of the output will be nxn where n is 2 3 1 0 -1 1 0 -1 1 0 -1 5 3 2 7 6 1 1 0 1 0 1 0 0 4 4 7 2 8 5 2 6 1 5 4 -1 -1 -1 6 4 1 3 4 2 2 1 5 3 3 | 1 7 0 8 1 2 3 7 3 2 1 6 4
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