Your input is a 58 * 91 RGB image, and you use a convolutional layer with 100 filters that are each 6 * 5 and with one bias parameter for each filter, using a stride of (4,6) and a total padding of 4. 1. What is the output shape? 2. What is the number of parameters (including the bias parameters)? 3. Suppose we further use a 3 * 4 max-pooling layer (with a stride of (3,4) and no padding) after the above convolutional layer. What is the output shape of the max-pooling layer?

Your input is a 58 * 91 RGB image, and you use a convolutional layer with 100 filters that are each 6 * 5 and with one bias parameter for each filter, using a stride of (4,6) and a total padding of 4. 1. What is the output shape? 2. What is the number of parameters (including the bias parameters)? 3. Suppose we further use a 3 * 4 max-pooling layer (with a stride of (3,4) and no padding) after the above convolutional layer. What is the output shape of the max-pooling layer?

Database System Concepts

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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

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Your input is a 58 * 91 RGB image, and you use a convolutional layer with 100 filters that are each 6 * 5 and with one bias parameter for each filter, using a stride of (4,6) and a total
padding of 4.
1. What is the output shape?
2. What is the number of parameters (including the bias parameters)?
3. Suppose we further use a 3 * 4 max-pooling layer (with a stride of (3,4) and no padding) after the above convolutional layer. What is the output shape of the max-pooling layer?

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