Supriyaa D, Riya Princy. C, Poorna Pushkala S, Ramya M
{"title":"Harnessing Machine Learning for Flora Disease Detection: A Survey of App-Based Approach","authors":"Supriyaa D, Riya Princy. C, Poorna Pushkala S, Ramya M","doi":"10.55041/ijsrem36648","DOIUrl":null,"url":null,"abstract":"This project aims to develop an AI-based plant disease detection app, leveraging various AI techniques such as machine learning and deep learning models. The primary focus lies in accurately identifying and segmenting diseased plant areas from healthy ones. For precise lesion segmentation, the app utilizes artificial intelligence methods like convolutional neural networks (CNNs) and image processing algorithms. By integrating segmentation and classification techniques, the app offers a comprehensive analysis of plant diseases based on visual symptoms such as discoloration, texture irregularities, and patterns. Users can categorize different plant diseases, receive recommendations for treatments or preventive measures, and conveniently purchase recommended products through the app. Key Words: Plant disease, disease detection, preventive measures, recommendation.","PeriodicalId":504501,"journal":{"name":"INTERANTIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENT","volume":"109 31","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2024-07-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"INTERANTIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENT","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.55041/ijsrem36648","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
This project aims to develop an AI-based plant disease detection app, leveraging various AI techniques such as machine learning and deep learning models. The primary focus lies in accurately identifying and segmenting diseased plant areas from healthy ones. For precise lesion segmentation, the app utilizes artificial intelligence methods like convolutional neural networks (CNNs) and image processing algorithms. By integrating segmentation and classification techniques, the app offers a comprehensive analysis of plant diseases based on visual symptoms such as discoloration, texture irregularities, and patterns. Users can categorize different plant diseases, receive recommendations for treatments or preventive measures, and conveniently purchase recommended products through the app. Key Words: Plant disease, disease detection, preventive measures, recommendation.