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Fisheries

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Mobile robotic platforms for the acoustic tracking of deep-sea demersal fishery resources.

Science robotics
Knowing the displacement capacity and mobility patterns of industrially exploited (i.e., fished) marine resources is key to establishing effective conservation management strategies in human-impacted marine ecosystems. Acquiring accurate behavioral i...

Application of machine learning to identify predators of stocked fish in Lake Ontario: using acoustic telemetry predation tags to inform management.

Journal of fish biology
Understanding predator-prey interactions and food web dynamics is important for ecosystem-based management in aquatic environments, as they experience increasing rates of human-induced changes, such as the addition and removal of fishes. To quantify ...

Machine learning for manually-measured water quality prediction in fish farming.

PloS one
Monitoring variables such as dissolved oxygen, pH, and pond temperature is a key aspect of high-quality fish farming. Machine learning (ML) techniques have been proposed to model the dynamics of such variables to improve the fish farmer's decision-ma...

Towards sustainable demersal fisheries: NepCon image acquisition system for automatic Nephrops norvegicus detection.

PloS one
Underwater video monitoring systems are being widely used in fisheries to investigate fish behavior in relation to fishing gear and fishing gear performance during fishing. Such systems can be useful to evaluate the catch composition as well. In deme...

An affordable and easy-to-use tool for automatic fish length and weight estimation in mariculture.

Scientific reports
Common aquaculture practices involve measuring fish biometrics at different growth stages, which is crucial for feeding regime management and for improving farmed fish welfare. Fish measurements are usually carried out manually on individual fish. Ho...

An Integrated Smart Pond Water Quality Monitoring and Fish Farming Recommendation Aquabot System.

Sensors (Basel, Switzerland)
The integration of cutting-edge technologies such as the Internet of Things (IoT), robotics, and machine learning (ML) has the potential to significantly enhance the productivity and profitability of traditional fish farming. Farmers using traditiona...

Enzymes from Fishery and Aquaculture Waste: Research Trends in the Era of Artificial Intelligence and Circular Bio-Economy.

Marine drugs
In the era of the blue bio-economy, which promotes the sustainable utilization and exploitation of marine resources for economic growth and development, the fisheries and aquaculture industries still face huge sustainability issues. One of the major ...

Leveraging deep learning and computer vision technologies to enhance management of coastal fisheries in the Pacific region.

Scientific reports
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. T...

Do China's ecological civilization advance demonstration zones inhibit fisheries' carbon emission intensity? A quasi-natural experiment using double machine learning and spatial difference-in-differences.

Journal of environmental management
China's National Ecological Civilization Demonstration Zone (NECDZ) policy has a significant role in ensuring national ecological security, and it is essential to investigate how the NECDZ policy affects the carbon emissions intensity of fisheries (C...

Attention-enhanced and integrated deep learning approach for fishing vessel classification based on multiple features.

Scientific reports
Effective fisheries management is the key to achieve sustainable fisheries globally, while accurate monitoring of fishing vessels is essential to improve the effectiveness of management measures. Self-reported information on vessel types is often lim...