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...
| Main Author: | |
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| Format: | Thesis |
| Language: | English |
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2011
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| Online Access: | http://eprints.usm.my/43123/ http://eprints.usm.my/43123/1/Pages_from_ENHANCED_AND_AUTOMATED.pdf |
| _version_ | 1848879743802277888 |
|---|---|
| author | Samma, Ali Salem Ali |
| author_facet | Samma, Ali Salem Ali |
| author_sort | Samma, Ali Salem Ali |
| building | USM Institutional Repository |
| collection | Online Access |
| 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. |
| first_indexed | 2025-11-15T17:52:05Z |
| format | Thesis |
| id | usm-43123 |
| institution | Universiti Sains Malaysia |
| institution_category | Local University |
| language | English |
| last_indexed | 2025-11-15T17:52:05Z |
| publishDate | 2011 |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | usm-431232018-12-10T07:49:23Z http://eprints.usm.my/43123/ Enhanced and automated approaches for fish recognition and classification system 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 NonPeerReviewed application/pdf en http://eprints.usm.my/43123/1/Pages_from_ENHANCED_AND_AUTOMATED.pdf Samma, Ali Salem Ali (2011) Enhanced and automated approaches for fish recognition and classification system. PhD thesis, Universiti Sains Malaysia. |
| spellingShingle | QA75.5-76.95 Electronic computers. Computer science Samma, Ali Salem Ali Enhanced and automated approaches for fish recognition and classification system |
| title | 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_short | Enhanced and automated approaches for fish recognition and classification system
|
| title_sort | enhanced and automated approaches for fish recognition and classification system |
| topic | QA75.5-76.95 Electronic computers. Computer science |
| url | http://eprints.usm.my/43123/ http://eprints.usm.my/43123/1/Pages_from_ENHANCED_AND_AUTOMATED.pdf |