Fish tracking based on YOLO and ByteTrack-Reference-Cited by-同舟云学术

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Fish tracking based on YOLO and ByteTrack

Published:2023-10-28 Issue: Volume: Page:1-5
ISSN:
Container-title:2023 16th International Congress on Image and Signal Processing, BioMedical Engineering and Informatics (CISP-BMEI)
language:
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Author:

Qian Zhi-Ming¹,Chen Xiang¹,Jiang Hua¹

Affiliation:

1. Chuxiong Normal University,School of Mathematics and Computer Science,Chuxiong,China

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10373215/10373216/10373254.pdf?arnumber=10373254

Reference15 articles.

1. Computer Vision Models in Intelligent Aquaculture with Emphasis on Fish Detection and Behavior Analysis: A Review

2. Recent advances of deep learning algorithms for aquacultural machine vision systems with emphasis on fish

3. Real-time nondestructive fish behavior detecting in mixed polyculture system using deep-learning and low-cost devices

4. Real-time detection of uneaten feed pellets in underwater images for aquaculture using an improved YOLO-V4 network

5. Automated Detection, Classification and Counting of Fish in Fish Passages With Deep Learning

Cited by 1 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Enhanced Tuna Detection and Automated Counting Method Utilizing Improved YOLOv7 and ByteTrack;Applied Sciences;2024-06-20

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