Author:
Hu Xuelong,Liu Yang,Zhao Zhengxi,Liu Jintao,Yang Xinting,Sun Chuanheng,Chen Shuhan,Li Bin,Zhou Chao
Funder
Beijing Municipal Science and Technology Commission
National Natural Science Foundation of China
Beijing Academy of Agriculture and Forestry Sciences
Ministry of Science and Technology of the People's Republic of China
Jiangsu Province Department of Human Resources and Social Security
Subject
Horticulture,Computer Science Applications,Agronomy and Crop Science,Forestry
Reference51 articles.
1. Automatic feeding control for dense aquaculture fish tanks;Atoum;Ieee Signal Proc. Let.,2015
2. Bochkovskiy, A., Wang, C. Y., Liao, H. Y. M., 2020. YOLOv4: Optimal Speed and Accuracy of Object Detection. arXiv preprint arXiv:2004.10934.
3. Cai, K. W., Miao, X. Y., Wang, W., Pang, H. S., Liu, Y., Song, J. Y., 2020. A modified YOLOv3 model for fish detection based on MobileNetv1 as backbone. Aquacult. Eng., 102117.
4. Fish protein hydrolysates: proximate composition, amino acid composition, antioxidant activities and applications: a review;Chalamaiah;Food Chem.,2012
5. Feed intake prediction model for group fish using the MEA-BP neural network in intensive aquaculture;Chen;Information Processing in Agriculture,2020
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