Recent advances of target tracking applications in aquaculture with emphasis on fish

Y Mei, B Sun, D Li, H Yu, H Qin, H Liu, N Yan… - … and Electronics in …, 2022 - Elsevier
In aquaculture, Behavioral monitoring of fish contributes to scientific management and
reduces the threat of loss from disease and stress. Fish tracking technology plays an …

[HTML][HTML] Applications of deep learning in fish habitat monitoring: A tutorial and survey

A Saleh, M Sheaves, D Jerry, MR Azghadi - Expert Systems with …, 2024 - Elsevier
Marine ecosystems and their fish habitats are becoming increasingly important due to their
integral role in providing a valuable food source and conservation outcomes. Due to their …

Computer vision and deep learning for fish classification in underwater habitats: A survey

A Saleh, M Sheaves, M Rahimi Azghadi - Fish and Fisheries, 2022 - Wiley Online Library
Marine scientists use remote underwater image and video recording to survey fish species
in their natural habitats. This helps them get a step closer towards understanding and …

A realistic fish-habitat dataset to evaluate algorithms for underwater visual analysis

A Saleh, IH Laradji, DA Konovalov, M Bradley… - Scientific Reports, 2020 - nature.com
Visual analysis of complex fish habitats is an important step towards sustainable fisheries for
human consumption and environmental protection. Deep Learning methods have shown …

Video image enhancement and machine learning pipeline for underwater animal detection and classification at cabled observatories

V Lopez-Vazquez, JM Lopez-Guede, S Marini… - Sensors, 2020 - mdpi.com
An understanding of marine ecosystems and their biodiversity is relevant to sustainable use
of the goods and services they offer. Since marine areas host complex ecosystems, it is …

Fish shoals behavior detection based on convolutional neural network and spatiotemporal information

F Han, J Zhu, B Liu, B Zhang, F Xie - IEEE access, 2020 - ieeexplore.ieee.org
Behavior is the first visible change in an animal species after exposure to its own or
environmental stressors and is a sensitive indicator. Fish are social animals, and the …

[HTML][HTML] Environmentally adaptive fish or no-fish classification for river video fish counters using high-performance desktop and embedded hardware

J Soom, V Pattanaik, M Leier, JA Tuhtan - Ecological Informatics, 2022 - Elsevier
Automated fish counters featuring robust, real-time computer vision capabilities can provide
a cost-effective means to count migrating freshwater fish. In this work, we propose a four …

Integrate MSRCR and mask R-CNN to recognize underwater creatures on small sample datasets

S Song, J Zhu, X Li, Q Huang - IEEE Access, 2020 - ieeexplore.ieee.org
The poor quality of optical imaging caused by the complex and varying underwater
environment is a significant challenge to underwater target recognition. Moreover, the …

[HTML][HTML] 融合SKNet 与YOLOv5 深度学习的养殖鱼群检测

赵梦, 于红, 李海清, 胥婧雯, 程思奇, 谷立帅… - 大连海洋大学 …, 2022 - xuebao.dlou.edu.cn
为解决真实养殖环境下, 水下成像模糊, 失真等导致鱼群检测准确率低的问题,
提出一种融合视觉注意力机制SKNet (selective kernel networks) 与YOLOv5 (you only look …

An intelligent and cost-effective remote underwater video device for fish size monitoring

G Coro, MB Walsh - Ecological Informatics, 2021 - Elsevier
Monitoring the size of key indicator species of fish is important to understand ecosystem
functions, anthropogenic stress, and population dynamics. Standard methodologies gather …