Advances in fisheries science through emerging observing technologies

Moustahfid, Hassan; Michaels, William; Alger, Brett; Gangopadhyay, Avijit; Brehmer, Patrice

doi:10.1109/ieeeconf38699.2020.9389452

Cited by 5 publications

(2 citation statements)

References 32 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Optic and sonar imaging rapidly came into play to directly estimate catches during capture (Silicon Intensified Target, SIT camera system, Krag et al, 2009;acoustic imaging, Ferro et al, 2007), then applied to observe species behavior in gears (Mortensen et al, 2017). Over the years, observing fishes became achievable in various conditions with the breadth of available technology that can be autonomously deployed for ecological and fisheries monitoring (Durden et al, 2016;Moustahfid et al, 2020).…”

Section: Observations Of Fish Behavior In Fishing Gearsmentioning

confidence: 99%

“…For ethologists, interpreting behaviors from visual observations come almost instantaneously. As developments of non-invasive and autonomous underwater video cameras continue to advance (Graham et al, 2004;Moustahfid et al, 2020), behavioral observations can now be derived from a plethora of high-resolution marine imagery and videos (Logares et al, 2021). The reach of human vision continues to extend as cameras can be used in most conditions (Shafait et al, 2016;Christensen et al, 2018;Jalal et al, 2020), such as light, dark and muddy underwater conditions, and can go to greater depth and longer periods (Torres et al, 2020;Bilodeau et al, 2022;Xia et al, 2022).…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Artificial intelligence for fish behavior recognition may unlock fishing gear selectivity

2023

View full text Add to dashboard Cite

Through the advancement of observation systems, our vision has far extended its reach into the world of fishes, and how they interact with fishing gears—breaking through physical boundaries and visually adapting to challenging conditions in marine environments. As marine sciences step into the era of artificial intelligence (AI), deep learning models now provide tools for researchers to process a large amount of imagery data (i.e., image sequence, video) on fish behavior in a more time-efficient and cost-effective manner. The latest AI models to detect fish and categorize species are now reaching human-like accuracy. Nevertheless, robust tools to track fish movements in situ are under development and primarily focused on tropical species. Data to accurately interpret fish interactions with fishing gears is still lacking, especially for temperate fishes. At the same time, this is an essential step for selectivity studies to advance and integrate AI methods in assessing the effectiveness of modified gears. We here conduct a bibliometric analysis to review the recent advances and applications of AI in automated tools for fish tracking, classification, and behavior recognition, highlighting how they may ultimately help improve gear selectivity. We further show how transforming external stimuli that influence fish behavior, such as sensory cues and gears as background, into interpretable features that models learn to distinguish remains challenging. By presenting the recent advances in AI on fish behavior applied to fishing gear improvements (e.g., Long Short-Term Memory (LSTM), Generative Adversarial Network (GAN), coupled networks), we discuss the advances, potential and limits of AI to help meet the demands of fishing policies and sustainable goals, as scientists and developers continue to collaborate in building the database needed to train deep learning models.

show abstract

Section: Observations Of Fish Behavior In Fishing Gearsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Artificial intelligence for fish behavior recognition may unlock fishing gear selectivity

2023

View full text Add to dashboard Cite

show abstract

Using Improved YOLOX for Underwater Object Recognition

Zhang

Peng

Zhang

2022

2022 5th International Conference on Pattern Recognition and Artificial Intelligence (PRAI)

View full text Add to dashboard Cite

Paired comparisons with quiet surface drones show evidence of fish behavioral response to motorized vessels during acoustic surveys in Lake Superior

Evans,

Rudstam,

Sethi

et al. 2024

Can. J. Fish. Aquat. Sci.

View full text Add to dashboard Cite

Acoustic surveys are important for fish stock assessments, but fish responses to survey vessels can bias acoustic estimates. We leveraged quiet uncrewed surface vessels (USVs) to characterize potential bias in acoustic surveys. Five conventional motorized ships overtook USVs from astern over 2 km transects at night in Lake Superior in 2022. We examined the difference in acoustic backscatter, average target depth, and average target strength (TS) between USV and motorized vessels. Although sound level measurements from the motorized vessels sometimes exceeded recommendations for scientific vessels, we did not detect differences in acoustic measures among survey vessels. However, the USVs recorded 2 dB higher acoustic backscatter and TS than motorized vessels, leading to ~15% higher fish densities with drones when using in situ TS and echo integration. Differences in fish density would increase to 30-60% if a standard TS value was applied. Target depth did not differ between USVs and motorized ships. These results are consistent with a change in orientation but not depth of insonified fish and limited horizontal avoidance of motorized survey vessels.

show abstract

Advances in fisheries science through emerging observing technologies

Cited by 5 publications

References 32 publications

Artificial intelligence for fish behavior recognition may unlock fishing gear selectivity

Artificial intelligence for fish behavior recognition may unlock fishing gear selectivity

Using Improved YOLOX for Underwater Object Recognition

Paired comparisons with quiet surface drones show evidence of fish behavioral response to motorized vessels during acoustic surveys in Lake Superior

Contact Info

Product

Resources

About