Please use this identifier to cite or link to this item:
https://hdl.handle.net/20.500.12348/5521
Harnessing Machine Learning to Estimate Aquaculture’s Contributions to the Economy of Southwest Bangladesh
Abstract
- Abstract accepted for presentation at the Annual Meeting of the World Aquaculture Society held in Singapore on 29 November to 2 December 2022. The presentation detailed the use of machine learning techniques to extract information from freely available satellite images and estimate the area of waterbodies used for aquaculture in seven districts in southern Bangladesh, one of country’s most important aquaculture zones producing fish for domestic markets and crustaceans for export.
- External link to download this item: https://cgspace.cgiar.org/handle/10568/127166
Collections
- Sustainable aquaculture [2702]
View/ Open
Date
- 2022
Author
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Belton, B.
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Haque, M.
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Ali, H.
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Nejadhashemi, A.
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Hernandez, R.
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Khondker, M.
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Ferriby, H.
Author(s) ORCID(s)
- Hazrat Alihttps://orcid.org/0000-0002-6303-1336
- Murshed-E-Jahan Khondkerhttps://orcid.org/0000-0001-9933-8631
AGROVOC Keywords
Type
- Other (Abstract)
Publisher
- WorldFish (WF)