A new multi-object tracking pipeline based on computer vision techniques for mussel farms

Author:

Zeng Dylon1,Liu Ivy1,Bi Ying2,Vennell Ross3,Briscoe Dana3,Xue Bing2,Zhang Mengjie2

Affiliation:

1. School of Mathematics and Statistics, Victoria University of Wellington, Wellington, New Zealand

2. School of Engineering and Computer Science, Victoria University of Wellington, Wellington, New Zealand

3. Coastal and Freshwater Group, Cawthron Institute, Nelson, New Zealand

Funder

the Science for Technological Innovation Challenge (SfTI) fund

MBIE Data Science SSIF Fund

Publisher

Informa UK Limited

Subject

Multidisciplinary

Cited by 5 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 Satellite Analytics for Mussel Platform Census Using a Machine-Learning Based Approach;Electronics;2024-07-15

2. Novel Algorithm to Detect, Classify, and Count Mussel Larvae in Seawater Samples Using Computer Vision;Applied Sciences;2024-06-12

3. A New Genetic Programming-Based Approach to Object Detection in Mussel Farm Images;2023 38th International Conference on Image and Vision Computing New Zealand (IVCNZ);2023-11-29

4. Improving Buoy Detection with Deep Transfer Learning for Mussel Farm Automation;2023 38th International Conference on Image and Vision Computing New Zealand (IVCNZ);2023-11-29

5. Buoy Detection under Extreme Low-light Illumination for Intelligent Mussel Farming;2023 38th International Conference on Image and Vision Computing New Zealand (IVCNZ);2023-11-29

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