{"title":"基于数字图像的作物和杂草分类研究进展","authors":"Radhika Kamath, Mamatha Balachandra, Srikanth Prabhu","doi":"10.1109/DISCOVER52564.2021.9663729","DOIUrl":null,"url":null,"abstract":"One of the major concern in the agricultural sector is the control of weeds. Weeds are capable of reducing the crop yield significantly and thus in curhuge loss. There are many ways of controlling weeds like using chemical herbicides, manual weeding, and using mechanical weeder. Overuse of chemical herbicides for weeds harms environment. Shortage of labors is a main problem with manual weeding. Mechanical weeding is not effective and is not suitable for some of the crops like direct-seeded rice fields. In recenty ears, technology is being explored in agriculture for the automatic detection and identification weeds from the digital images. This is useful in recommending specific herbicides and thus reducing overuse of herbicides and herbicide-resistant weeds. Thus contributing to site-specific weed management. This paper reviews some of the important research works carried out for the classification of crop and weeds from the digital images. In addition, some of the important future research scopes are discussed in this paper.","PeriodicalId":413789,"journal":{"name":"2021 IEEE International Conference on Distributed Computing, VLSI, Electrical Circuits and Robotics (DISCOVER)","volume":"139 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2021-11-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Classification of Crop and Weed from Digital Images: A Review\",\"authors\":\"Radhika Kamath, Mamatha Balachandra, Srikanth Prabhu\",\"doi\":\"10.1109/DISCOVER52564.2021.9663729\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"One of the major concern in the agricultural sector is the control of weeds. Weeds are capable of reducing the crop yield significantly and thus in curhuge loss. There are many ways of controlling weeds like using chemical herbicides, manual weeding, and using mechanical weeder. Overuse of chemical herbicides for weeds harms environment. Shortage of labors is a main problem with manual weeding. Mechanical weeding is not effective and is not suitable for some of the crops like direct-seeded rice fields. In recenty ears, technology is being explored in agriculture for the automatic detection and identification weeds from the digital images. This is useful in recommending specific herbicides and thus reducing overuse of herbicides and herbicide-resistant weeds. Thus contributing to site-specific weed management. This paper reviews some of the important research works carried out for the classification of crop and weeds from the digital images. In addition, some of the important future research scopes are discussed in this paper.\",\"PeriodicalId\":413789,\"journal\":{\"name\":\"2021 IEEE International Conference on Distributed Computing, VLSI, Electrical Circuits and Robotics (DISCOVER)\",\"volume\":\"139 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2021-11-19\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2021 IEEE International Conference on Distributed Computing, VLSI, Electrical Circuits and Robotics (DISCOVER)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/DISCOVER52564.2021.9663729\",\"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 International Conference on Distributed Computing, VLSI, Electrical Circuits and Robotics (DISCOVER)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/DISCOVER52564.2021.9663729","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Classification of Crop and Weed from Digital Images: A Review
One of the major concern in the agricultural sector is the control of weeds. Weeds are capable of reducing the crop yield significantly and thus in curhuge loss. There are many ways of controlling weeds like using chemical herbicides, manual weeding, and using mechanical weeder. Overuse of chemical herbicides for weeds harms environment. Shortage of labors is a main problem with manual weeding. Mechanical weeding is not effective and is not suitable for some of the crops like direct-seeded rice fields. In recenty ears, technology is being explored in agriculture for the automatic detection and identification weeds from the digital images. This is useful in recommending specific herbicides and thus reducing overuse of herbicides and herbicide-resistant weeds. Thus contributing to site-specific weed management. This paper reviews some of the important research works carried out for the classification of crop and weeds from the digital images. In addition, some of the important future research scopes are discussed in this paper.