Zobrazeno 1 - 10
of 7 727
pro vyhledávání: '"pest detection"'
Autor:
Xiong, Peng1 (AUTHOR), Zhang, Cong1 (AUTHOR) Carole_Waterssna@mail.co, He, Linfeng1 (AUTHOR), Zhan, Xiaoyun1 (AUTHOR), Han, Yuantao1 (AUTHOR)
Publikováno v:
PLoS ONE. 11/7/2024, Vol. 19 Issue 11, p1-20. 20p.
Autor:
Wang, Wanqing1 (AUTHOR) 202131901244@nwnu.edu.cn, Fu, Haoyue2 (AUTHOR) 202131901244@nwnu.edu.cn
Publikováno v:
Information (2078-2489). Sep2024, Vol. 15 Issue 9, p519. 12p.
Autor:
Bompani, Luca, Crupi, Luca, Palossi, Daniele, Baldoni, Olmo, Brunelli, Davide, Conti, Francesco, Rusci, Manuele, Benini, Luca
The codling moth pest poses a significant threat to global crop production, with potential losses of up to 80% in apple orchards. Special camera-based sensor nodes are deployed in the field to record and transmit images of trapped insects to monitor
Externí odkaz:
http://arxiv.org/abs/2408.15911
Publikováno v:
Scientific Reports, Vol 14, Iss 1, Pp 1-18 (2024)
Abstract Timely and accurate detection of rice pests is highly important for pest control, as well as for improving rice yield and quality. However, owing to the high interclass similarity, significant intraclass age differences, and complex backgrou
Externí odkaz:
https://doaj.org/article/cc63dc6ff27e486db5b1d37259e6420b
This paper presents a threshold-based automated pea weevil detection system, developed as part of the Microsoft FarmVibes project. Based on Internet-of-Things (IoT) and computer vision, the system is designed to monitor and manage pea weevil populati
Externí odkaz:
http://arxiv.org/abs/2410.19813
Autor:
Zheng, Yong1,2 (AUTHOR), Zheng, Weiheng1,2 (AUTHOR) zhengweiheng@xmut.edu.cn, Du, Xia1 (AUTHOR)
Publikováno v:
Scientific Reports. 12/2/2024, Vol. 14 Issue 1, p1-18. 18p.
Autor:
Mu, Junlin1 (AUTHOR) mjl19970127@163.com, Sun, Linlin1,2 (AUTHOR) sunlinlin@sdau.edu.cn, Ma, Bo1 (AUTHOR) 2023010151@sdau.edu.cn, Liu, Ruofei1 (AUTHOR) 19860912870@163.com, Liu, Shuangxi1 (AUTHOR) shuangxiliu168@163.com, Hu, Xianliang3 (AUTHOR) 2022010103@sdau.edu.cn, Zhang, Hongjian1,2 (AUTHOR) zhanghongji_an@163.com, Wang, Jinxing1,4 (AUTHOR) zhanghongji_an@163.com
Publikováno v:
AgriEngineering. Dec2024, Vol. 6 Issue 4, p4688-4703. 16p.
Autor:
Li, Kai-Run1 (AUTHOR) viperl1@stu.hunau.edu.cn, Duan, Li-Jun1 (AUTHOR) duanlijunagr@163.com, Deng, Yang-Jun1 (AUTHOR) dengyangjun@hunau.edu.cn, Liu, Jin-Ling2 (AUTHOR) liujinling@hunau.edu.cn, Long, Chen-Feng1 (AUTHOR), Zhu, Xing-Hui1 (AUTHOR) dengyangjun@hunau.edu.cn
Publikováno v:
Agronomy. Oct2024, Vol. 14 Issue 10, p2303. 14p.
Publikováno v:
Scientific Reports, Vol 14, Iss 1, Pp 1-15 (2024)
Abstract Pest detection is important for crop cultivation. Crop leaf is the main place of pest invasion. Current technologies to detect crop pests have constraints, such as low efficiency, storage demands and limited precision. Image segmentation is
Externí odkaz:
https://doaj.org/article/d357c9dfcdc74e0eb2f8c095d024caf5
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