A Proposed Biologically Inspired Model for Object Recognition

Object recognition has attracted the attention of many researchers as it is considered as one of the most important problems in computer vision. Two main approaches have been utilized to develop object recognition solutions i.e. machine and biological vision. Many algorithms have been developed i...

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Main Authors: Hamada , R. H. Al-Absi, Azween, Abdullah
Format: Book Section
Published: ACM 2009
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Online Access:http://eprints.utp.edu.my/802/1/PID1193295.pdf
http://eprints.utp.edu.my/802/
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spelling my.utp.eprints.8022017-01-19T08:25:41Z A Proposed Biologically Inspired Model for Object Recognition Hamada , R. H. Al-Absi Azween, Abdullah QA75 Electronic computers. Computer science Object recognition has attracted the attention of many researchers as it is considered as one of the most important problems in computer vision. Two main approaches have been utilized to develop object recognition solutions i.e. machine and biological vision. Many algorithms have been developed in machine vision. Recently, Biology has inspired computer scientist to map the features of the human and primate’s visual systems into computational models. Some of these models are based on the feedforward mechanism of information processing in cortex; however, the performance of these models has been affected by the increase of clutter in the scene. Another mechanism of information processing in cortex is called the feedback. This mechanism has also been mapped into computational models. However, the results were also not satisfying. In this paper an object recognition model based on the integration of the feedforward and feedback functions in the visual cortex is proposed. ACM 2009 Book Section PeerReviewed application/pdf http://eprints.utp.edu.my/802/1/PID1193295.pdf Hamada , R. H. Al-Absi and Azween, Abdullah (2009) A Proposed Biologically Inspired Model for Object Recognition. In: Visual Informatics: Bridging Research and Practice. ACM. http://eprints.utp.edu.my/802/
institution Universiti Teknologi Petronas
building UTP Resource Centre
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Teknologi Petronas
content_source UTP Institutional Repository
url_provider http://eprints.utp.edu.my/
topic QA75 Electronic computers. Computer science
spellingShingle QA75 Electronic computers. Computer science
Hamada , R. H. Al-Absi
Azween, Abdullah
A Proposed Biologically Inspired Model for Object Recognition
description Object recognition has attracted the attention of many researchers as it is considered as one of the most important problems in computer vision. Two main approaches have been utilized to develop object recognition solutions i.e. machine and biological vision. Many algorithms have been developed in machine vision. Recently, Biology has inspired computer scientist to map the features of the human and primate’s visual systems into computational models. Some of these models are based on the feedforward mechanism of information processing in cortex; however, the performance of these models has been affected by the increase of clutter in the scene. Another mechanism of information processing in cortex is called the feedback. This mechanism has also been mapped into computational models. However, the results were also not satisfying. In this paper an object recognition model based on the integration of the feedforward and feedback functions in the visual cortex is proposed.
format Book Section
author Hamada , R. H. Al-Absi
Azween, Abdullah
author_facet Hamada , R. H. Al-Absi
Azween, Abdullah
author_sort Hamada , R. H. Al-Absi
title A Proposed Biologically Inspired Model for Object Recognition
title_short A Proposed Biologically Inspired Model for Object Recognition
title_full A Proposed Biologically Inspired Model for Object Recognition
title_fullStr A Proposed Biologically Inspired Model for Object Recognition
title_full_unstemmed A Proposed Biologically Inspired Model for Object Recognition
title_sort proposed biologically inspired model for object recognition
publisher ACM
publishDate 2009
url http://eprints.utp.edu.my/802/1/PID1193295.pdf
http://eprints.utp.edu.my/802/
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