Increasing robustness against background noise: visual pattern recognition by a neocognitron

DOI10.1016/J.NEUNET.2011.03.017zbMath1263.68150OpenAlexW2023630909WikidataQ51580021 ScholiaQ51580021MaRDI QIDQ1952561

Kunihiko Fukushima

Publication date: 31 May 2013

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

Full work available at URL: https://doi.org/10.1016/j.neunet.2011.03.017

zbMATH Keywords

feature extractionroot-mean-squarevisual pattern recognitionbackground noiseneocognitronsubtractive inhibition

Mathematics Subject Classification ID

Learning and adaptive systems in artificial intelligence (68T05) Pattern recognition, speech recognition (68T10)

Related Items (2)

Training multi-layered neural network neocognitron ⋮ Spike-Timing-Dependent Construction

Cites Work

• Unnamed Item
• Neocognition: A self-organizing neural network model for a mechanism of pattern recognition unaffected by shift in position
• Invariant recognition of feature combinations in the visual system

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