most citedA method for detecting dead fish on large water surfaces based on improved YOLOv10

2 citations · 3 across the 2 of their papers we have counts for

collaborators

5 papers

cs.CV2025

Progressive Multimodal Interaction Network for Reliable Quantification of Fish Feeding Intensity in Aquaculture

Shulong Zhang, Mingyuan Yao, Jiayin Zhao +3

Accurate quantification of fish feeding intensity is crucial for precision feeding in aquaculture, as it directly affects feed utilization and farming efficiency. Although multimod…

cs.CV2025

A Comprehensive Review of Fish Feeding Behavior Analysis in Aquaculture: Tasks, Techniques, and Applications

Shulong Zhang, Daoliang Li, Jiayin Zhao +3

Fish feeding behavior analysis is a key foundation for intelligent feeding and precision aquaculture management, and plays an important role in improving feed utilization efficienc…

cs.CV2024

FMRFT: Fusion Mamba and DETR for Query Time Sequence Intersection Fish Tracking

Mingyuan Yao, Yukang Huo, Qingbin Tian +5

Early detection of abnormal fish behavior caused by disease or hunger can be achieved through fish tracking using deep learning techniques, which holds significant value for indust…

cs.CV20242 cited

A method for detecting dead fish on large water surfaces based on improved YOLOv10

Qingbin Tian, Yukang Huo, Mingyuan Yao +1

Dead fish frequently appear on the water surface due to various factors. If not promptly detected and removed, these dead fish can cause significant issues such as water quality de…

cs.CV20241 cited

FA-YOLO: Research On Efficient Feature Selection YOLO Improved Algorithm Based On FMDS and AGMF Modules

Yukang Huo, Mingyuan Yao, Qingbin Tian +3

Over the past few years, the YOLO series of models has emerged as one of the dominant methodologies in the realm of object detection. Many studies have advanced these baseline mode…