基于YOLOv5的害虫识别系统

Sheng Yu, Shangzhu Jin, Jun Peng, Zhishu Zhao, Ming Yang Hou, Wenjun Cheng
{"title":"基于YOLOv5的害虫识别系统","authors":"Sheng Yu, Shangzhu Jin, Jun Peng, Zhishu Zhao, Ming Yang Hou, Wenjun Cheng","doi":"10.1109/ICCICC53683.2021.9811296","DOIUrl":null,"url":null,"abstract":"Forest pests and diseases are a global problem. The key to control forestry diseases is to accurately identify the species and severity of pests. How to use artificial intelligence and image recognition technology to detect forestry pests is an important challenge and opportunity. This paper presents a new method for forestry pest identification based on YOLOv5 algorithm. In addition, in order to unify the system and expand the flexibility of the future system, we adopted the B/S/S structure to develop the pest identification system. The system uses the camera to shoot images and transmits the data to the background recognition. The experimental results show that our system can detect the target pests more accurately and conveniently, which is helpful for the actual prevention and control of forestry pests.","PeriodicalId":101653,"journal":{"name":"2021 IEEE 20th International Conference on Cognitive Informatics & Cognitive Computing (ICCI*CC)","volume":"48 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2021-10-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Pest Identification System based on YOLOv5\",\"authors\":\"Sheng Yu, Shangzhu Jin, Jun Peng, Zhishu Zhao, Ming Yang Hou, Wenjun Cheng\",\"doi\":\"10.1109/ICCICC53683.2021.9811296\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Forest pests and diseases are a global problem. The key to control forestry diseases is to accurately identify the species and severity of pests. How to use artificial intelligence and image recognition technology to detect forestry pests is an important challenge and opportunity. This paper presents a new method for forestry pest identification based on YOLOv5 algorithm. In addition, in order to unify the system and expand the flexibility of the future system, we adopted the B/S/S structure to develop the pest identification system. The system uses the camera to shoot images and transmits the data to the background recognition. The experimental results show that our system can detect the target pests more accurately and conveniently, which is helpful for the actual prevention and control of forestry pests.\",\"PeriodicalId\":101653,\"journal\":{\"name\":\"2021 IEEE 20th International Conference on Cognitive Informatics & Cognitive Computing (ICCI*CC)\",\"volume\":\"48 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2021-10-29\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2021 IEEE 20th International Conference on Cognitive Informatics & Cognitive Computing (ICCI*CC)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICCICC53683.2021.9811296\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2021 IEEE 20th International Conference on Cognitive Informatics & Cognitive Computing (ICCI*CC)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICCICC53683.2021.9811296","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0

摘要

森林病虫害是一个全球性问题。准确识别有害生物的种类和严重程度是防治林业病害的关键。如何利用人工智能和图像识别技术检测林业有害生物是一个重要的挑战和机遇。提出了一种基于YOLOv5算法的林业有害生物识别新方法。此外,为了统一系统,扩大未来系统的灵活性,我们采用B/S/S结构开发害虫识别系统。该系统利用摄像头拍摄图像并将数据传输到后台识别。实验结果表明,该系统能更准确、方便地检测出目标害虫,有助于林业害虫的实际防治。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Pest Identification System based on YOLOv5
Forest pests and diseases are a global problem. The key to control forestry diseases is to accurately identify the species and severity of pests. How to use artificial intelligence and image recognition technology to detect forestry pests is an important challenge and opportunity. This paper presents a new method for forestry pest identification based on YOLOv5 algorithm. In addition, in order to unify the system and expand the flexibility of the future system, we adopted the B/S/S structure to develop the pest identification system. The system uses the camera to shoot images and transmits the data to the background recognition. The experimental results show that our system can detect the target pests more accurately and conveniently, which is helpful for the actual prevention and control of forestry pests.
求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
自引率
0.00%
发文量
0
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:604180095
Book学术官方微信