{"title":"基于决策树的叶片病害检测与分类","authors":"B. Rajesh, M. V. Sai Vardhan, L. Sujihelen","doi":"10.1109/ICOEI48184.2020.9142988","DOIUrl":null,"url":null,"abstract":"Agricultural productivity is very dependent on the economy. Plant diseases play an important role in agriculture because plant diseases are very natural and failure to care will have serious consequences for plants and therefore affect the quality, quantity, or productivity of the product. Timely and accurate diagnosis of leaf diseases plays a major part in preventing loss in productivity and loss or reduction of agricultural products. Detection of plant diseases by automated techniques is beneficial because it reduces monitoring efforts on large plants and detects an indication of disease which occurs when they came on the leaves of plants very early. More researchers have proposed leaf disease detection techniques. The existing systems have less detection accuracy. This proposed system uses a decision tree to identify and classify leaf disease and increases its detection accuracy with less time compared with the existing system.","PeriodicalId":267795,"journal":{"name":"2020 4th International Conference on Trends in Electronics and Informatics (ICOEI)(48184)","volume":"116 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2020-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"22","resultStr":"{\"title\":\"Leaf Disease Detection and Classification by Decision Tree\",\"authors\":\"B. Rajesh, M. V. Sai Vardhan, L. Sujihelen\",\"doi\":\"10.1109/ICOEI48184.2020.9142988\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Agricultural productivity is very dependent on the economy. Plant diseases play an important role in agriculture because plant diseases are very natural and failure to care will have serious consequences for plants and therefore affect the quality, quantity, or productivity of the product. Timely and accurate diagnosis of leaf diseases plays a major part in preventing loss in productivity and loss or reduction of agricultural products. Detection of plant diseases by automated techniques is beneficial because it reduces monitoring efforts on large plants and detects an indication of disease which occurs when they came on the leaves of plants very early. More researchers have proposed leaf disease detection techniques. The existing systems have less detection accuracy. This proposed system uses a decision tree to identify and classify leaf disease and increases its detection accuracy with less time compared with the existing system.\",\"PeriodicalId\":267795,\"journal\":{\"name\":\"2020 4th International Conference on Trends in Electronics and Informatics (ICOEI)(48184)\",\"volume\":\"116 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2020-06-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"22\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2020 4th International Conference on Trends in Electronics and Informatics (ICOEI)(48184)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICOEI48184.2020.9142988\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2020 4th International Conference on Trends in Electronics and Informatics (ICOEI)(48184)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICOEI48184.2020.9142988","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Leaf Disease Detection and Classification by Decision Tree
Agricultural productivity is very dependent on the economy. Plant diseases play an important role in agriculture because plant diseases are very natural and failure to care will have serious consequences for plants and therefore affect the quality, quantity, or productivity of the product. Timely and accurate diagnosis of leaf diseases plays a major part in preventing loss in productivity and loss or reduction of agricultural products. Detection of plant diseases by automated techniques is beneficial because it reduces monitoring efforts on large plants and detects an indication of disease which occurs when they came on the leaves of plants very early. More researchers have proposed leaf disease detection techniques. The existing systems have less detection accuracy. This proposed system uses a decision tree to identify and classify leaf disease and increases its detection accuracy with less time compared with the existing system.