AIMC Topic: Fishes

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Impact of deep learning and post-processing algorithms performances on biodiversity metrics assessed on videos.

PloS one
Assessing the escalating biodiversity crisis, driven by climate change, habitat destruction, and exploitation, necessitates efficient monitoring strategies to assess species presence and abundance across diverse habitats. Video-based surveys using re...

Little-to-no industrial fishing occurs in fully and highly protected marine areas.

Science (New York, N.Y.)
There is a widespread perception that illegal fishing is common in marine protected areas (MPAs) due to strong incentives for poaching and the high cost of monitoring and enforcement. Using artificial intelligence and satellite-based Earth observatio...

Automated seafood freshness detection and preservation analysis using machine learning and paper-based pH sensors.

Scientific reports
Seafood, including fish, prawns and various marine products, is a critical component of global nutrition due to its high protein content, essential fatty acids, vitamins and minerals. Traditional methods for assessing seafood freshness such as sensor...

The intelligent evaluation model of the English humanistic landscape in agricultural industrial parks by the SPEAKING model: From the perspective of fish-vegetable symbiosis in new agriculture.

PloS one
To more accurately capture the expression of the English humanistic landscape in agricultural industrial parks under the emerging agricultural paradigm of fish-vegetable symbiosis, and to address the limitations of unscientific evaluation standards a...

Predicting the Site-Specific Toxicity of Metals to Fishes Using a New Machine Learning-Based Approach.

Environmental science & technology
Fishes of various trophic levels play an important role in the stability and balance of aquatic ecosystems. Metal contaminants can impair the survival and population fitness of fish at elevated concentrations. When universal water quality criteria (W...

Optimal feature selection and model explanation for reef fish sound classification.

Philosophical transactions of the Royal Society of London. Series B, Biological sciences
Fish produce a wide variety of sounds that contribute to the soundscapes of aquatic environments. In reef systems, these sounds are important acoustic cues for various ecological processes. Artificial intelligence methods to detect, classify and iden...

A novel approach combining YOLO and DeepSORT for detecting and counting live fish in natural environments through video.

PloS one
Applying Artificial Intelligence (AI) to the monitoring of live fish in natural environments represents a promising approach to the sustainable management of aquatic resources. Detecting and counting fish in water through video analysis is crucial fo...

Underwater bionic undulating fins incorporating thickness effects: hydrodynamic performance and optimal thickness variation rate analysis.

Bioinspiration & biomimetics
In response to the urgent issues faced by current bionic undulating fin robot propulsion mechanisms, such as low working efficiency, insufficient swimming speed, ignoring thickness parameters, and the need for further improvement in biomimetic degree...

Investigating the effect of morphology on the terrestrial gaits of amphibious fish using a reconfigurable robot.

Bioinspiration & biomimetics
The relationship between morphology and locomotion performance in amphibious fish remains poorly understood, particularly in axial-appendage-based and appendage-based movements. To address this, we introduce Polymander, a reconfigurable robot capable...

SwinFishNet: A Swin Transformer-based approach for automatic fish species classification using transfer learning.

PloS one
The fish market is a crucial industry for both domestic economies and the global seafood trade. Accurate fish species classification (FSC) plays a significant role in ensuring sustainability, improving food safety, and optimizing market efficiency. T...