Counting and measuring the size and stomach fullness levels for an intelligent shrimp farming system-Reference-Cited by-同舟云学术

Counting and measuring the size and stomach fullness levels for an intelligent shrimp farming system

Published:2023-10-18 Issue:1 Volume:35 Page:
ISSN:0954-0091
Container-title:Connection Science
language:en
Short-container-title:Connection Science

Author:

Lee Yu-Kai¹,Lin Bo-Yi¹,Weng Tien-Hsiung¹,Huang Chien-Kang²,Liu Chen³,Liu Chih-Chin¹,Lin Shih-Shun⁴,Wang Han-Ching⁵⁶

Affiliation:

1. Department of Computer Science and Information Engineering, Providence University, Taichung, Taiwan, ROC

2. Department of Engineering Science and Ocean Engineering, National Taiwan University, Taipei, Taiwan, ROC

3. Department of Electrical and Computer Engineering, Clarkson University, New York, USA

4. Institute of Biotechnology, National Taiwan University, Taipei, Taiwan, ROC

5. Department of Biotechnology and Bioindustry Sciences, National Cheng Kung University, Tainan, Taiwan, ROC

6. International Center for Scientific Development of Shrimp Aquaculture, National Cheng Kung University, Tainan, Taiwan, ROC

Publisher

Informa UK Limited

Subject

Artificial Intelligence,Human-Computer Interaction,Software

Link

https://www.tandfonline.com/doi/pdf/10.1080/09540091.2023.2268878

Reference49 articles.

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2. Application of dissemination plastic ponds technology to Litopenaeus vannamei shrimp culture as a solution for aquaculture activities in narrow soil;Astiyani W. P.;Aquaculture, Aquarium, Conservation & Legislation,2022

3. Stomach and gut content of Long Neck Croacker–Pseudotolithus typus (Bleeker,1863) from Lagos Lagoon, Nigera

4. Bochkovskiy A. Wang C.-Y. & Liao H.-Y. M. (2020). Yolov4: Optimal speed and accuracy of object detection. arXiv preprint arXiv:2004.10934 .

5. R2FA-Det: Delving into High-Quality Rotatable Boxes for Ship Detection in SAR Images