Glossary Library

Technical GlossaryDeep Learning

Feature Map

The spatial activation representation produced by a convolution layer through specific filters.

A feature map is one of the central structures that reveals what local patterns a CNN has extracted from an image or other grid-like data. Each filter is sensitive to a different kind of structure and produces its own activation map. As the network deepens, these maps evolve into more abstract visual representations. It is a key concept for understanding how CNNs perceive data.

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Representation Learning

An approach in which informative, discriminative, and task-relevant internal representations are learned automatically from raw data.

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Non-negative Matrix Factorization

A dimensionality reduction technique that produces part-based and interpretable representations in non-negative data.

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Autoencoder-Based Dimensionality Reduction

An approach that learns lower-dimensional representations of data through neural-network-based compression.