Developing deep learning methods for aquaculture applications
Saleh, Alzayat (2020) Developing deep learning methods for aquaculture applications. Masters (Research) thesis, James Cook University.
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Abstract
Alzayat Saleh developed a computer vision framework that can aid aquaculture experts in analyzing fish habitats. In particular, he developed a labelling efficient method of training a CNN-based fish-detector and also developed a model that estimates the fish weight directly from its image.
| Item ID: | 68786 |
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| Item Type: | Thesis (Masters (Research)) |
| Keywords: | aquaculture, Asian seabass, barramundi, Lates calcarifer, computer vision, image processing, weight estimation |
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| Copyright Information: | Copyright © 2020 Alzayat Saleh. |
| Additional Information: | Four publications arising from this thesis are stored in ResearchOnline@JCU, at the time of processing. Please see the Related URLs. The publications are: Chapter 3: Konovalov, Dmitry A., Saleh, Alzayat, Bradley, Michael, Sankupellay, Mangalam, Marini, Simone, and Sheaves, Marcus (2019) Underwater fish detection with weak multi-domain supervision. In: Proceedings of the International Joint Conference on Neural Networks. From: 2019 IJCNN: International Joint Conference on Neural Networks, 14-19 July 2019, Budapest, Hungary. Chapter 4: Saleh, Alzayat, Laradji, Issam H., Konovalov, Dmitry A., Bradley, Michael, Vazquez, David, and Sheaves, Marcus (2020) A realistic fish-habitat dataset to evaluate algorithms for underwater visual analysis. Scientific Reports, 10. 14671. Chapter 5: Konovalov, Dmitry A., Saleh, Alzayat, Domingos, Jose A., White, Ron D., and Jerry, Dean R. (2018) Estimating mass of harvested Asian seabass Lates calcarifer from images. World Journal of Engineering and Technology, 6 (3). pp. 15-23. Chapter 6: Konovalov, Dmitry A., Saleh, Alzayat, Efremova, Dina B., Domingos, Jose A., and Jerry, Dean R. (2019) Automatic weight estimation of harvested fish from images. In: Proceedings of the International Conference on Digital Image Computing. pp. 308-314. From: DICTA 2019: International Conference on Digital Image Computing: Techniques and Applications, 2-4 December 2019, Perth, WA, Australia. |
| Date Deposited: | 23 Jul 2021 05:25 |
| FoR Codes: | 46 INFORMATION AND COMPUTING SCIENCES > 4603 Computer vision and multimedia computation > 460306 Image processing @ 35% 46 INFORMATION AND COMPUTING SCIENCES > 4611 Machine learning > 461199 Machine learning not elsewhere classified @ 35% 30 AGRICULTURAL, VETERINARY AND FOOD SCIENCES > 3005 Fisheries sciences > 300501 Aquaculture @ 30% |
| SEO Codes: | 10 ANIMAL PRODUCTION AND ANIMAL PRIMARY PRODUCTS > 1003 Fisheries - wild caught > 100305 Wild caught fin fish (excl. tuna) @ 35% 18 ENVIRONMENTAL MANAGEMENT > 1805 Marine systems and management > 180502 Assessment and management of pelagic marine ecosystems @ 35% 18 ENVIRONMENTAL MANAGEMENT > 1805 Marine systems and management > 180504 Marine biodiversity @ 30% |
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