Discover how to calculate the output volume of a Convolutional Neural Network (CNN) when given specific parameters like input size, filter count, filter size, stride, and padding. Learn the step-by-step process to determine the output dimensions accurately.
Table of Contents
Question
You have an input volume that is 127x127x16, and convolve it with 32 filters of 5×5, using a stride of 2 and no padding. What is the output volume?
A. 123x123x32
B. 123x123x16
C. 62x62x16
D. 62x62x32
Answer
D. 62x62x32
Explanation
When dealing with Convolutional Neural Networks (CNNs), calculating the output volume after applying a convolution operation is crucial for understanding how data progresses through the network. In this scenario, we have an input volume of 127x127x16, and we apply 32 filters of size 5×5 with a stride of 2 and no padding. Let’s break down how to calculate the output dimensions:
Input Dimensions:
Height: 127
Width: 127
Depth: 16
Filter Specifications:
Number of Filters: 32
Filter Size: 5×5
Convolution Parameters:
Stride: 2
Padding: 0 (No Padding)
Therefore, the output volume after convolution is 62×62×32, making option D (62x62x32) the correct answer.
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