Advancing Fisheries Research and Management with Computer Vision: A Survey of Recent Developments and Pending Challenges DOI Creative Commons
Jesse Eickholt, Jonathan Gregory,

Kavya Vemuri

et al.

Fishes, Journal Year: 2025, Volume and Issue: 10(2), P. 74 - 74

Published: Feb. 12, 2025

The field of computer vision has progressed rapidly over the past ten years, with noticeable improvements in techniques to detect, locate, and classify objects. Concurrent these advances, improved accessibility through machine learning software libraries sparked investigations applications across multiple domains. In areas fisheries research management, efforts have centered on localization fish classification by species, as such tools can estimate health, size, movement populations. To aid interpretation for management tasks, a survey recent literature was conducted. contrast prior reviews, this focuses employed evaluation metrics datasets well challenges associated applying context. Misalignment between commonly used mischaracterizes efficacy emerging tasks. Aqueous, turbid, variable lighted deployment settings further complicate use generalizability reported results. Informed inherent challenges, culling surveillance data, exploratory data collection remote settings, selective passage traps are presented opportunities future research.

Language: Английский

Advancing Fisheries Research and Management with Computer Vision: A Survey of Recent Developments and Pending Challenges DOI Creative Commons
Jesse Eickholt, Jonathan Gregory,

Kavya Vemuri

et al.

Fishes, Journal Year: 2025, Volume and Issue: 10(2), P. 74 - 74

Published: Feb. 12, 2025

The field of computer vision has progressed rapidly over the past ten years, with noticeable improvements in techniques to detect, locate, and classify objects. Concurrent these advances, improved accessibility through machine learning software libraries sparked investigations applications across multiple domains. In areas fisheries research management, efforts have centered on localization fish classification by species, as such tools can estimate health, size, movement populations. To aid interpretation for management tasks, a survey recent literature was conducted. contrast prior reviews, this focuses employed evaluation metrics datasets well challenges associated applying context. Misalignment between commonly used mischaracterizes efficacy emerging tasks. Aqueous, turbid, variable lighted deployment settings further complicate use generalizability reported results. Informed inherent challenges, culling surveillance data, exploratory data collection remote settings, selective passage traps are presented opportunities future research.

Language: Английский

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