EℓI-chan for Intermediate Features

We propose an EℓI-chan, Emergent ℓocal Indicator Mechanism, to model the representation and self-organization of intermediate features in the visual pathway. This model is motivated by the orientation specificity in the primary visual cortex. Our simulations of EℓI-chan demonstrate that local indica...

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Main Author:	TING, Christopher
Format:	text
Language:	English
Published:	Institutional Knowledge at Singapore Management University 1993
Subjects:	Physical Sciences and Mathematics
Online Access:	https://ink.library.smu.edu.sg/lkcsb_research/779 https://doi.org/10.1109/IJCNN.1993.714234
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Institution:	Singapore Management University
Language:	English

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spelling	sg-smu-ink.lkcsb_research-17782017-06-14T02:02:33Z EℓI-chan for Intermediate Features TING, Christopher We propose an EℓI-chan, Emergent ℓocal Indicator Mechanism, to model the representation and self-organization of intermediate features in the visual pathway. This model is motivated by the orientation specificity in the primary visual cortex. Our simulations of EℓI-chan demonstrate that local indicators of the locations of intermediate features emerge, and they become the seeds for unsupervised learning and pattern recognition; EℓI-chan predicts those portions of the input imagery where intermediate features potentially exist. Hence, EℓI-chan can be used to define a set of intermediate features for adaptation, and the onwards processing in a hierarchical pattern recognition system. 1993-10-01T07:00:00Z text https://ink.library.smu.edu.sg/lkcsb_research/779 info:doi/10.1109/IJCNN.1993.714234 https://doi.org/10.1109/IJCNN.1993.714234 Research Collection Lee Kong Chian School Of Business eng Institutional Knowledge at Singapore Management University Physical Sciences and Mathematics
institution	Singapore Management University
building	SMU Libraries
continent	Asia
country	Singapore Singapore
content_provider	SMU Libraries
collection	InK@SMU
language	English
topic	Physical Sciences and Mathematics
spellingShingle	Physical Sciences and Mathematics TING, Christopher EℓI-chan for Intermediate Features
description	We propose an EℓI-chan, Emergent ℓocal Indicator Mechanism, to model the representation and self-organization of intermediate features in the visual pathway. This model is motivated by the orientation specificity in the primary visual cortex. Our simulations of EℓI-chan demonstrate that local indicators of the locations of intermediate features emerge, and they become the seeds for unsupervised learning and pattern recognition; EℓI-chan predicts those portions of the input imagery where intermediate features potentially exist. Hence, EℓI-chan can be used to define a set of intermediate features for adaptation, and the onwards processing in a hierarchical pattern recognition system.
format	text
author	TING, Christopher
author_facet	TING, Christopher
author_sort	TING, Christopher
title	EℓI-chan for Intermediate Features
title_short	EℓI-chan for Intermediate Features
title_full	EℓI-chan for Intermediate Features
title_fullStr	EℓI-chan for Intermediate Features
title_full_unstemmed	EℓI-chan for Intermediate Features
title_sort	eℓi-chan for intermediate features
publisher	Institutional Knowledge at Singapore Management University
publishDate	1993
url	https://ink.library.smu.edu.sg/lkcsb_research/779 https://doi.org/10.1109/IJCNN.1993.714234
_version_	1770569688420450304

EℓI-chan for Intermediate Features

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