Enhanced and automated approaches for fish recognition and classification system.
| dc.contributor.author | Samma, Ali Salem Ali | |
| dc.date.accessioned | 2018-12-10T07:39:37Z | |
| dc.date.available | 2018-12-10T07:39:37Z | |
| dc.date.issued | 2011-06 | |
| dc.description.abstract | 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. | en_US |
| dc.identifier.uri | http://hdl.handle.net/123456789/7247 | |
| dc.language.iso | en | en_US |
| dc.publisher | Universiti Sains Malaysia | en_US |
| dc.subject | Recognition | en_US |
| dc.subject | Classification | en_US |
| dc.title | Enhanced and automated approaches for fish recognition and classification system. | en_US |
| dc.type | Thesis | en_US |
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