Assume that an input RGB image below is entering a Convolutional Neural Network: 6 4 7. 3. 1 1 3 8. 4 2 1 2 8. 1 4 5 5 1 13 6. 3 6 8 2 4 1 3 34 2 3 3 27 1 5 3 4 1 38 2 7 2 o 3 15 3 1 72 7 4 3 3 5 3 5 4 2 6. 1 7 0 3 1 2 7 2 3 2 5 2 1 1 4 We use the following vertical edge filter to convolve with the image. 10 -1 -1 1 -1 0-1 1 1 -1 -1 0-1 -1 -1 f the padding size is 3 and the stride is also 3. The size of the output will be nxn where n is
Assume that an input RGB image below is entering a Convolutional Neural Network: 6 4 7. 3. 1 1 3 8. 4 2 1 2 8. 1 4 5 5 1 13 6. 3 6 8 2 4 1 3 34 2 3 3 27 1 5 3 4 1 38 2 7 2 o 3 15 3 1 72 7 4 3 3 5 3 5 4 2 6. 1 7 0 3 1 2 7 2 3 2 5 2 1 1 4 We use the following vertical edge filter to convolve with the image. 10 -1 -1 1 -1 0-1 1 1 -1 -1 0-1 -1 -1 f the padding size is 3 and the stride is also 3. The size of the output will be nxn where n is
Database System Concepts
7th Edition
ISBN:9780078022159
Author:Abraham Silberschatz Professor, Henry F. Korth, S. Sudarshan
Publisher:Abraham Silberschatz Professor, Henry F. Korth, S. Sudarshan
Chapter1: Introduction
Section: Chapter Questions
Problem 1PE
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Transcribed Image Text:Assume that an input RGB image below is entering a Convolutional Neural Network:
4
6
4 5
7
4
7
1
3
2
4
8
1
1
4 25
7 21 1
8 4 7 0
4 2 3
2
5
6 1
5 4
2 3 26
1
1
3
3 4
3 1
7
8
5
2 7 1
5
7 05 3
6.
2
1
|3 1
7
17
2 3 2 o
3 4
4
3
5
6.
1 1
5 2
We use the following vertical edge filter to convolve with the image.
1
-1
1
-1
1
-1
-1
-1
-1
1
-1
-1
1
1
-1
If the padding size is 3 and the stride is also 3. The size of the output will be nxn where n is
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