AIMC Topic: Fishes

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Multimodal fish maw type recognition based on Wasserstein generative adversarial network combined with gradient penalty and spectral fusion.

Spectrochimica acta. Part A, Molecular and biomolecular spectroscopy Nov 10, 2024
There are many types of fish maw with significantly varying prices. The specific type directly affects its market value and medicinal efficacy. This paper proposes a fish maw type recognition method based on Wasserstein generative adversarial network...
Spectroscopy, Near-Infrared Spectrum Analysis, Raman Fishes Female Animals Male Neural Networks, Computer Algorithms
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Hyperspectral imaging and deep learning for parasite detection in white fish under industrial conditions.

Scientific reports Nov 9, 2024
Parasites in fish muscle present a significant problem for the seafood industry in terms of both quality and health and safety, but the low contrast between parasites and fish tissue makes them exceedingly difficult to detect. The traditional method ...
Seafood Hyperspectral Imaging Nematoda Fish Diseases Fishes Food Parasitology Animals Deep Learning
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Enhancing eco-sensing in aquatic environments: Fish jumping behavior automatic recognition using YOLOv5.

Aquatic toxicology (Amsterdam, Netherlands) Nov 1, 2024
Contemporary research on ichthyological behavior predominantly investigates underwater environments. However, the intricate nature of aquatic ecosystems often hampers subaqueous observations of fish behavior due to interference. Transitioning the obs...
Ecosystem Environmental Monitoring Fishes Neural Networks, Computer Animals Behavior, Animal
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A Bio-Inspired Magnetic Soft Robotic Fish for Efficient Solar-Energy Driven Water Purification.

Small methods Oct 24, 2024
Solar-driven water evaporation is a promising solution for global water scarcity but is still facing challenges due to its substantial energy requirements. Here, a magnetic soft robotic bionic fish is developed by combining magnetic nanoparticles (Fe...
Chitosan Robotics Magnetite Nanoparticles Water Purification Animals Hydrophobic and Hydrophilic Interactions Solar Energy Bionics Molecular Dynamics Simulation Acrylic Resins Fishes
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An integrated three-stream network model for discriminating fish feeding intensity using multi-feature analysis and deep learning.

PloS one Oct 21, 2024
Feed costs constitute a significant part of the expenses in the aquaculture industry. However, feeding practices in fish farming often rely on the breeder's experience, leading to feed wastage and environmental pollution. To achieve precision in feed...
Fishes Feeding Behavior Neural Networks, Computer Animals Deep Learning Aquaculture Animal Feed
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Machine learning models to predict the bioaccessibility of parent and substituted polycyclic aromatic hydrocarbons (PAHs) in food: Impact on accurate health risk assessment.

Journal of hazardous materials Oct 9, 2024
Food intake is the primary pathway for polycyclic aromatic hydrocarbons (PAHs) to enter the human body. Once ingested, PAHs tend to accumulate, posing health risks. To accurately assess the risk of PAHs from food, concentrations of 10 parent PAHs (PP...
Food Contamination Fishes Seafood Polycyclic Aromatic Hydrocarbons Shellfish Machine Learning Animals Risk Assessment Humans
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Machine learning-enabled attapulgite/polyimide nanofiber composite aerogels-based colorimetric sensor array for real-time monitoring of balsa fish freshness.

Food chemistry Sep 20, 2024
This paper presents the development and application of attapulgite/polyimide nanofiber composite aerogels (ATP/PI NFAs) integrated with a range of acid-base indicators, fabricated using electrospinning and freeze-drying technologies. A detailed chara...
Gels Nanofibers Magnesium Compounds Fishes Seafood Machine Learning Silicon Compounds Animals Colorimetry
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Leveraging deep learning and computer vision technologies to enhance management of coastal fisheries in the Pacific region.

Scientific reports Sep 8, 2024
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...
Deep Learning Fishes Conservation of Natural Resources Artificial Intelligence Animals Pacific Ocean Fisheries Ecosystem
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Computer-Simulated Virtual Image Datasets to Train Machine Learning Models for Non-Invasive Fish Detection in Recirculating Aquaculture.

Sensors (Basel, Switzerland) Sep 7, 2024
Artificial Intelligence (AI) and Machine Learning (ML) can assist producers to better manage recirculating aquaculture systems (RASs). ML is a data-intensive process, and model performance primarily depends on the quality of training data. Relatively...
Aquaculture Fishes Computer Simulation Artificial Intelligence Animals Machine Learning Image Processing, Computer-Assisted
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Towards reliable data: Validation of a machine learning-based approach for microplastics analysis in marine organisms using Nile red staining.

Marine pollution bulletin Sep 5, 2024
Microplastic (MP) research faces challenges due to costly, time-consuming, and error-prone analysis techniques. Additionally, the variability in data quality across studies limits their comparability. This study addresses the critical need for reliab...
Oxazines Aquatic Organisms Environmental Monitoring Microplastics Water Pollutants, Chemical Fishes Machine Learning Plastics Gastrointestinal Tract Animals Mytilus edulis
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