Feature maps are the outputs generated by convolutional layers in Convolutional Neural Networks (CNNs) that represent the presence of various features in the input data. Each feature map corresponds to a specific filter or kernel applied to the input image, highlighting certain aspects like edges, textures, or patterns. This process is crucial for feature extraction and helps in building hierarchical representations, allowing the network to learn complex structures and relationships within the data.
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