L. Rahunathan, D. Sivabalaselvamani, E.S. Elakkiya, M. Madhumitha, K. Kumaresh
{"title":"基于神经网络和机器学习技术的豆叶病害识别","authors":"L. Rahunathan, D. Sivabalaselvamani, E.S. Elakkiya, M. Madhumitha, K. Kumaresh","doi":"10.1109/ICSMDI57622.2023.00098","DOIUrl":null,"url":null,"abstract":"Plant leaf diseases have increased in prevalence recently, making it necessary to conduct accurate research. Bean leaf diseases can be prevented from spreading by earlier detection and accurate identification. Diseases of bean leaves have negatively affected bean yield and quality. There are two types of diseases predicted in bean leaves: angular leaf spots and rust. This work includes a contrast between deep learning algorithms and machine learning algorithms-based approaches such as CNN (Convolutional Neural Networks/ConvNet) and its predefined models, K-Nearest Neighbor in short KNN, Support Vector Machine can also have written as SVM, Multinomial Logistic Regression that automate the identification of leaf diseases in bean plant species. As far as known, no one has offered a comparison study for identifying bean leaf disease.","PeriodicalId":373017,"journal":{"name":"2023 3rd International Conference on Smart Data Intelligence (ICSMDI)","volume":"25 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2023-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Recognition of Bean Leaf Diseases Using Neural Network and Machine Learning Techniques\",\"authors\":\"L. Rahunathan, D. Sivabalaselvamani, E.S. Elakkiya, M. Madhumitha, K. Kumaresh\",\"doi\":\"10.1109/ICSMDI57622.2023.00098\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Plant leaf diseases have increased in prevalence recently, making it necessary to conduct accurate research. Bean leaf diseases can be prevented from spreading by earlier detection and accurate identification. Diseases of bean leaves have negatively affected bean yield and quality. There are two types of diseases predicted in bean leaves: angular leaf spots and rust. This work includes a contrast between deep learning algorithms and machine learning algorithms-based approaches such as CNN (Convolutional Neural Networks/ConvNet) and its predefined models, K-Nearest Neighbor in short KNN, Support Vector Machine can also have written as SVM, Multinomial Logistic Regression that automate the identification of leaf diseases in bean plant species. As far as known, no one has offered a comparison study for identifying bean leaf disease.\",\"PeriodicalId\":373017,\"journal\":{\"name\":\"2023 3rd International Conference on Smart Data Intelligence (ICSMDI)\",\"volume\":\"25 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2023-03-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2023 3rd International Conference on Smart Data Intelligence (ICSMDI)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICSMDI57622.2023.00098\",\"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 3rd International Conference on Smart Data Intelligence (ICSMDI)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICSMDI57622.2023.00098","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Recognition of Bean Leaf Diseases Using Neural Network and Machine Learning Techniques
Plant leaf diseases have increased in prevalence recently, making it necessary to conduct accurate research. Bean leaf diseases can be prevented from spreading by earlier detection and accurate identification. Diseases of bean leaves have negatively affected bean yield and quality. There are two types of diseases predicted in bean leaves: angular leaf spots and rust. This work includes a contrast between deep learning algorithms and machine learning algorithms-based approaches such as CNN (Convolutional Neural Networks/ConvNet) and its predefined models, K-Nearest Neighbor in short KNN, Support Vector Machine can also have written as SVM, Multinomial Logistic Regression that automate the identification of leaf diseases in bean plant species. As far as known, no one has offered a comparison study for identifying bean leaf disease.