An Automatic Detection and Counting Method for Fish Lateral Line Scales of Underwater Fish Based on Improved YOLOv5
The lateral line scales of fish are an important phenotype of fish species. As an important countable feature, the accurate and effective counting of lateral line scales is an important reference standard for breeding, determining the growth status of fish, and identifying fish species. At present,...
Main Authors: | Huihui Yu, Zimao Wang, Hanxiang Qin, Yingyi Chen |
---|---|
Format: | Article |
Language: | English |
Published: |
IEEE
2023-01-01
|
Series: | IEEE Access |
Subjects: | |
Online Access: | https://ieeexplore.ieee.org/document/10360813/ |
Similar Items
-
Fish counting through underwater fish detection using deep learning techniques
by: Sundari VEERAPPAN, et al.
Published: (2023-12-01) -
Fish Target Detection in Underwater Blurred Scenes Based on Improved YOLOv5
by: Fei Wu, et al.
Published: (2023-01-01) -
Detection and Identification of Fish Skin Health Status Referring to Four Common Diseases Based on Improved YOLOv4 Model
by: Gangyi Yu, et al.
Published: (2023-03-01) -
An FSFS-Net Method for Occluded and Aggregated Fish Segmentation from Fish School Feeding Images
by: Ling Yang, et al.
Published: (2023-05-01) -
Fish sonar image recognition algorithm based on improved YOLOv5
by: Bowen Xing, et al.
Published: (2024-01-01)