精准农业:无人机监控作物图像分割与损失评估

P. Patidar, D. Tomar, R. Pateriya, Y. K. Sharma
{"title":"精准农业:无人机监控作物图像分割与损失评估","authors":"P. Patidar, D. Tomar, R. Pateriya, Y. K. Sharma","doi":"10.1109/ICSCCC58608.2023.10176980","DOIUrl":null,"url":null,"abstract":"Agriculture is the most important source of livelihood. Crop segmentation has become an important role in precision agriculture which helps farmers to make decisions about crop damage and its production. However, it's a challenging task to achieve precision in the agriculture field. Drone Surveillance helps to achieve that crop yield assessment, crop damage, crop health, and other parameters. This paper focuses on image segmentation of crops, classified into categories like sparse and dense crops with the multitemporal data image taken by Drone. This model proposed and studied shows the loss percentage in crop identification by image segmentation process, it helps farmers to get good compensation for crops to survey through Drone (UAV) techniques. A detailed analysis with outcome of thisis explained further.","PeriodicalId":359466,"journal":{"name":"2023 Third International Conference on Secure Cyber Computing and Communication (ICSCCC)","volume":"49 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2023-05-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Precision Agriculture: Crop Image Segmentation and Loss Evaluation through Drone Surveillance\",\"authors\":\"P. Patidar, D. Tomar, R. Pateriya, Y. K. Sharma\",\"doi\":\"10.1109/ICSCCC58608.2023.10176980\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Agriculture is the most important source of livelihood. Crop segmentation has become an important role in precision agriculture which helps farmers to make decisions about crop damage and its production. However, it's a challenging task to achieve precision in the agriculture field. Drone Surveillance helps to achieve that crop yield assessment, crop damage, crop health, and other parameters. This paper focuses on image segmentation of crops, classified into categories like sparse and dense crops with the multitemporal data image taken by Drone. This model proposed and studied shows the loss percentage in crop identification by image segmentation process, it helps farmers to get good compensation for crops to survey through Drone (UAV) techniques. A detailed analysis with outcome of thisis explained further.\",\"PeriodicalId\":359466,\"journal\":{\"name\":\"2023 Third International Conference on Secure Cyber Computing and Communication (ICSCCC)\",\"volume\":\"49 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2023-05-26\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2023 Third International Conference on Secure Cyber Computing and Communication (ICSCCC)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICSCCC58608.2023.10176980\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2023 Third International Conference on Secure Cyber Computing and Communication (ICSCCC)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICSCCC58608.2023.10176980","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

农业是最重要的民生来源。作物分割在精准农业中发挥着重要的作用,它可以帮助农民对作物的损害和产量进行决策。然而,在农业领域实现精准化是一项具有挑战性的任务。无人机监视有助于实现作物产量评估、作物损害、作物健康和其他参数。本文主要对农作物进行图像分割,利用无人机拍摄的多时相数据图像,将农作物分为稀疏和密集两类。提出并研究的模型显示了图像分割过程中作物识别的损失百分比,帮助农民通过无人机(UAV)技术对作物进行调查,获得良好的补偿。并对结果进行了详细的分析。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Precision Agriculture: Crop Image Segmentation and Loss Evaluation through Drone Surveillance
Agriculture is the most important source of livelihood. Crop segmentation has become an important role in precision agriculture which helps farmers to make decisions about crop damage and its production. However, it's a challenging task to achieve precision in the agriculture field. Drone Surveillance helps to achieve that crop yield assessment, crop damage, crop health, and other parameters. This paper focuses on image segmentation of crops, classified into categories like sparse and dense crops with the multitemporal data image taken by Drone. This model proposed and studied shows the loss percentage in crop identification by image segmentation process, it helps farmers to get good compensation for crops to survey through Drone (UAV) techniques. A detailed analysis with outcome of thisis explained further.
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