Feature Map
In the context of deep learning, a feature map is a representation of the input data generated by a convolutional neural network (CNN). It is a 3D array of values that correspond to the activation levels of a set of learned filters applied to the input data. Each filter extracts a specific feature from the input data, and the resulting feature maps are concatenated to form the output of a CNN layer. Feature maps are used to capture the spatial relationships between the input data and the learned features, allowing the network to identify complex patterns and objects in the data.
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