Real-time and effective detection of agricultural pest using an improved YOLOv5 network
Author:
Funder
National Natural Science Foundation of China
Publisher
Springer Science and Business Media LLC
Subject
Information Systems
Link
https://link.springer.com/content/pdf/10.1007/s11554-023-01264-0.pdf
Reference35 articles.
1. Ebrahimi, M.A., Khoshtaghaza, M.H., Minaei, S., Jamshidi, B.: Vision-based pest detection based on SVM classification method. Comput. Electron. Agric. 137, 52–58 (2017)
2. Gadekallu, T.R., Rajput, D.S., Reddy, M.P.K., Lakshmanna, K., Bhattacharya, S., Singh, S., Alazab, M.: A novel PCA-whale optimization-based deep neural network model for classification of tomato plant diseases using GPU. J. Real-Time Image Proc. 18, 1383–1396 (2021)
3. Yun, W., Kumar, J.P., Lee, S., Kim, D.S., Cho, B.K.: Deep learning-based system development for black pine bast scale detection. Sci. Rep. 12(1), 1–10 (2022)
4. Lippi, M., Bonucci, N., Carpio, R. F., Contarini, M., Speranza, S., Gasparri, A.: A yolo-based pest detection system for precision agriculture. In: 2021 29th Mediterranean Conference on Control and Automation (MED) pp. 342–347 (June) (2021)
5. Jiao, L., Dong, S., Zhang, S., Xie, C., Wang, H.: AF-RCNN: An anchor-free convolutional neural network for multi-categories agricultural pest detection. Comput. Electron. Agric. 174, 105522 (2020)
Cited by 7 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. An intelligent system for high-density small target pest identification and infestation level determination based on an improved YOLOv5 model;Expert Systems with Applications;2024-04
2. Automatic detection and counting of planthoppers on white flat plate images captured by AR glasses for planthopper field survey;Computers and Electronics in Agriculture;2024-03
3. Real-time canola damage detection: An end-to-end framework with semi-automatic crusher and lightweight ShuffleNetV2_YOLOv5s;Smart Agricultural Technology;2024-03
4. Sugarcane Bud Detection Using YOLOv5;Communications in Computer and Information Science;2024
5. MFSPest: A multi-scale feature selection network for light-trapped agricultural pest detection;Journal of Intelligent & Fuzzy Systems;2023-10-04
1.学者识别学者识别
2.学术分析学术分析
3.人才评估人才评估
"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370
www.globalauthorid.com
TOP
Copyright © 2019-2024 北京同舟云网络信息技术有限公司 京公网安备11010802033243号 京ICP备18003416号-3