What is the feature map in Convolutional Neural Networks?
Answer
A feature map is the output of a convolution operation in a Convolutional Neural Network (CNN) that highlights where specific features appear in the input, enabling the network to understand patterns and structures in input data.
Feature Map in CNNs:
(1) Output of a Filter: It’s the 2D (or 3D) output generated when a single convolutional filter slides across the input data.
(2) Highlighting a Specific Feature: Each feature map represents the spatial locations and strengths where a particular pattern or characteristic (e.g., a vertical edge, a specific texture, a corner) is detected in the input.
(3) Multiple Feature Maps per Layer: A convolutional layer typically uses multiple filters, with each filter producing its unique feature map.
The following example shows feature map examples calculated with different filters on the original image.
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