Learning Slowness in a Sparse Model of Invariant Feature Detection

DOI10.1162/NECO_a_00743zbMath1414.92011OpenAlexW2162955556WikidataQ48177928 ScholiaQ48177928MaRDI QIDQ5380289

Thusitha N. Chandrapala, Bertram Emil Shi

Publication date: 4 June 2019

Published in: Neural Computation (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1162/neco_a_00743

zbMATH Keywords

generative adaptive subspace self-organizing mapnaturalistic image sequenceprimary visual cortical complex cells

Mathematics Subject Classification ID

Neural networks for/in biological studies, artificial life and related topics (92B20)

Uses Software

• GTM

Cites Work

• Unnamed Item
• Natural image statistics. A probabilistic approach to early computational vision.
• Developments of the generative topographic mapping
• Emergence of invariant-feature detectors in the adaptive-subspace self-organizing map
• Slow Feature Analysis: Unsupervised Learning of Invariances
• Independent component analysis applied to feature extraction from colour and stereo images

This page was built for publication: Learning Slowness in a Sparse Model of Invariant Feature Detection