JF-YOLO: the jellyfish bloom detector based on deep learning
Author:
Funder
Natural Science Foundation of Hebei Province
National Natural Science Foundation of China
Publisher
Springer Science and Business Media LLC
Subject
Computer Networks and Communications,Hardware and Architecture,Media Technology,Software
Link
https://link.springer.com/content/pdf/10.1007/s11042-023-15465-z.pdf
Reference48 articles.
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2. An L, Wang L, Ou D, Jia C, Li W, Ding Y, You C, Liao J, Huang H (2021) The ecological mechanisms of Acetes blooms as a threat to the security of cooling systems in coastal nuclear power plants. J Coast Conserv 25 (6):1–10
3. Baliarsingh S K, Lotliker A A, Srichandan S, Samanta A, Kumar N, Nair TM B (2020) A review of jellyfish aggregations, focusing on India’s coastal waters. Ecol Process 9(1):1–9
4. Barrado C, Fuentes J A, Salamí E, Royo P, Olariaga A D, López J, Fuentes V L, Gili J M, Pastor E (2014) Jellyfish monitoring on coastlines using remote piloted aircraft. In: IOP conference series: Earth and environmental science, vol 17. IOP Publishing, p 012195
5. Bochkovskiy A, Wang C-Y, Liao H-Y M (2020) Yolov4: optimal speed and accuracy of object detection. arXiv:2004.10934
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