Enhanced and automated approaches for fish recognition and classification system

Pengecaman dan pengelasan imej ikan dengan darjah ketepatan dan kecekapan yang tinggi boleh menjadi satu tugas yang sukar kerana ikan mempunyai persamaan yang sangat tinggi dengan latar belakangnya, kehilangan beberapa ciri ikan, dan kos komputan yang tinggi. Recognition and classification of fi...

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Bibliographic Details
Main Author:	Samma, Ali Salem Ali
Format:	Thesis
Language:	English
Published:	2011
Subjects:	QA75.5-76.95 Electronic computers Computer science
Online Access:	http://eprints.usm.my/43123/1/Pages_from_ENHANCED_AND_AUTOMATED.pdf
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id	my-usm-ep.43123
record_format	uketd_dc
spelling	my-usm-ep.431232018-12-10T07:49:23Z Enhanced and automated approaches for fish recognition and classification system 2011-06 Samma, Ali Salem Ali QA75.5-76.95 Electronic computers. Computer science Pengecaman dan pengelasan imej ikan dengan darjah ketepatan dan kecekapan yang tinggi boleh menjadi satu tugas yang sukar kerana ikan mempunyai persamaan yang sangat tinggi dengan latar belakangnya, kehilangan beberapa ciri ikan, dan kos komputan yang tinggi. Recognition and classification of fish images with high degree of accuracy and efficiency can be a difficult task due to fish being very similar to the background, missing of some features and high cost of computation. 2011-06 Thesis http://eprints.usm.my/43123/ http://eprints.usm.my/43123/1/Pages_from_ENHANCED_AND_AUTOMATED.pdf application/pdf en public phd doctoral Universiti Sains Malaysia Pusat Pengajian Sains Komputer
institution	Universiti Sains Malaysia
collection	USM Institutional Repository
language	English
topic	QA75.5-76.95 Electronic computers Computer science
spellingShingle	QA75.5-76.95 Electronic computers Computer science Samma, Ali Salem Ali Enhanced and automated approaches for fish recognition and classification system
description	Pengecaman dan pengelasan imej ikan dengan darjah ketepatan dan kecekapan yang tinggi boleh menjadi satu tugas yang sukar kerana ikan mempunyai persamaan yang sangat tinggi dengan latar belakangnya, kehilangan beberapa ciri ikan, dan kos komputan yang tinggi. Recognition and classification of fish images with high degree of accuracy and efficiency can be a difficult task due to fish being very similar to the background, missing of some features and high cost of computation.
format	Thesis
qualification_name	Doctor of Philosophy (PhD.)
qualification_level	Doctorate
author	Samma, Ali Salem Ali
author_facet	Samma, Ali Salem Ali
author_sort	Samma, Ali Salem Ali
title	Enhanced and automated approaches for fish recognition and classification system
title_short	Enhanced and automated approaches for fish recognition and classification system
title_full	Enhanced and automated approaches for fish recognition and classification system
title_fullStr	Enhanced and automated approaches for fish recognition and classification system
title_full_unstemmed	Enhanced and automated approaches for fish recognition and classification system
title_sort	enhanced and automated approaches for fish recognition and classification system
granting_institution	Universiti Sains Malaysia
granting_department	Pusat Pengajian Sains Komputer
publishDate	2011
url	http://eprints.usm.my/43123/1/Pages_from_ENHANCED_AND_AUTOMATED.pdf
_version_	1747821168940810240

Enhanced and automated approaches for fish recognition and classification system

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