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Leveraging deep learning and computer vision technologies to enhance management of coastal fisheries in the Pacific region
by
Rota, Manibua
, Gislard, Sebastien
, Li, Owen
, Jalam, Shivam
, Joy, Lucy A.
, Andrew, Neil L.
, Halford, Andrew R.
, Fatongiatau, Viliami
, Sokach, Ada H. M.
, Shedrawi, George
, Fepuleai, Faasulu
, Nikiari, Beia
, Tiitii, Sapeti
, Steenbergen, Dirk J.
, Vigga, Bernard
, Molai, Chris
, Sami, Abel P.
, Magron, Franck
, Bosserelle, Pauline
in
631/158/2458
/ 631/158/672
/ 704/829/826
/ Animals
/ Artificial Intelligence
/ Artisanal fisheries
/ Automation
/ Capacity development
/ Co-management
/ Coastal fisheries
/ Coastal fisheries management
/ Computer vision
/ Conservation of Natural Resources - methods
/ Data poor fisheries
/ Decision making
/ Deep Learning
/ Ecosystem
/ Environmental monitoring
/ Fish barriers
/ Fisheries
/ Fisheries - economics
/ Fisheries management
/ Fishery development
/ Fishes
/ Fishing
/ Fishing communities
/ Humanities and Social Sciences
/ Information processing
/ Monitoring
/ Monitoring systems
/ multidisciplinary
/ Pacific Ocean
/ Science
/ Science (multidisciplinary)
2024
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Leveraging deep learning and computer vision technologies to enhance management of coastal fisheries in the Pacific region
by
Rota, Manibua
, Gislard, Sebastien
, Li, Owen
, Jalam, Shivam
, Joy, Lucy A.
, Andrew, Neil L.
, Halford, Andrew R.
, Fatongiatau, Viliami
, Sokach, Ada H. M.
, Shedrawi, George
, Fepuleai, Faasulu
, Nikiari, Beia
, Tiitii, Sapeti
, Steenbergen, Dirk J.
, Vigga, Bernard
, Molai, Chris
, Sami, Abel P.
, Magron, Franck
, Bosserelle, Pauline
in
631/158/2458
/ 631/158/672
/ 704/829/826
/ Animals
/ Artificial Intelligence
/ Artisanal fisheries
/ Automation
/ Capacity development
/ Co-management
/ Coastal fisheries
/ Coastal fisheries management
/ Computer vision
/ Conservation of Natural Resources - methods
/ Data poor fisheries
/ Decision making
/ Deep Learning
/ Ecosystem
/ Environmental monitoring
/ Fish barriers
/ Fisheries
/ Fisheries - economics
/ Fisheries management
/ Fishery development
/ Fishes
/ Fishing
/ Fishing communities
/ Humanities and Social Sciences
/ Information processing
/ Monitoring
/ Monitoring systems
/ multidisciplinary
/ Pacific Ocean
/ Science
/ Science (multidisciplinary)
2024
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Leveraging deep learning and computer vision technologies to enhance management of coastal fisheries in the Pacific region
by
Rota, Manibua
, Gislard, Sebastien
, Li, Owen
, Jalam, Shivam
, Joy, Lucy A.
, Andrew, Neil L.
, Halford, Andrew R.
, Fatongiatau, Viliami
, Sokach, Ada H. M.
, Shedrawi, George
, Fepuleai, Faasulu
, Nikiari, Beia
, Tiitii, Sapeti
, Steenbergen, Dirk J.
, Vigga, Bernard
, Molai, Chris
, Sami, Abel P.
, Magron, Franck
, Bosserelle, Pauline
in
631/158/2458
/ 631/158/672
/ 704/829/826
/ Animals
/ Artificial Intelligence
/ Artisanal fisheries
/ Automation
/ Capacity development
/ Co-management
/ Coastal fisheries
/ Coastal fisheries management
/ Computer vision
/ Conservation of Natural Resources - methods
/ Data poor fisheries
/ Decision making
/ Deep Learning
/ Ecosystem
/ Environmental monitoring
/ Fish barriers
/ Fisheries
/ Fisheries - economics
/ Fisheries management
/ Fishery development
/ Fishes
/ Fishing
/ Fishing communities
/ Humanities and Social Sciences
/ Information processing
/ Monitoring
/ Monitoring systems
/ multidisciplinary
/ Pacific Ocean
/ Science
/ Science (multidisciplinary)
2024
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Leveraging deep learning and computer vision technologies to enhance management of coastal fisheries in the Pacific region
Journal Article
Leveraging deep learning and computer vision technologies to enhance management of coastal fisheries in the Pacific region
2024
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Overview
This paper presents the design and development of a coastal fisheries monitoring system that harnesses artificial intelligence technologies. Application of the system across the Pacific region promises to revolutionize coastal fisheries management. The program is built on a centralized, cloud-based monitoring system to automate data extraction and analysis processes. The system leverages YoloV4, OpenCV, and ResNet101 to extract information from images of fish and invertebrates collected as part of in-country monitoring programs overseen by national fisheries authorities. As of December 2023, the system has facilitated automated identification of over six hundred nearshore finfish species, and automated length and weight measurements of more than 80,000 specimens across the Pacific. The system integrates other key fisheries monitoring data such as catch rates, fishing locations and habitats, volumes, pricing, and market characteristics. The collection of these metrics supports much needed rapid fishery assessments. The system’s co-development with national fisheries authorities and the geographic extent of its application enables capacity development and broader local inclusion of fishing communities in fisheries management. In doing so, the system empowers fishers to work with fisheries authorities to enable data-informed decision-making for more effective adaptive fisheries management. The system overcomes historically entrenched technical and financial barriers in fisheries management in many Pacific island communities.
Publisher
Nature Publishing Group UK,Nature Publishing Group,Nature Portfolio
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