Computational object recognition: a biologically motivated approach

DOI10.1007/s00422-008-0281-6zbMath1266.68185OpenAlexW2030186353WikidataQ37352836 ScholiaQ37352836MaRDI QIDQ2376404

Tim C. Kietzmann, Martin Riedmiller, Sascha Lange

Publication date: 21 June 2013

Published in: Biological Cybernetics (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1007/s00422-008-0281-6

zbMATH Keywords

object recognitionincremental learningfeature selectionbiologically inspired computer visionview-based object representations

Mathematics Subject Classification ID

Neural networks for/in biological studies, artificial life and related topics (92B20) Pattern recognition, speech recognition (68T10) Machine vision and scene understanding (68T45)

Uses Software

• COIL-100

Cites Work

• The internal representation of solid shape with respect to vision
• Modeling perceptual learning: Difficulties and how they can be overcome
• Learning viewpoint invariant object representations using a temporal coherence principle
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