{"title":"Design of plant disease detection system: A transfer learning approach work in progress","authors":"Boikobo Tlhobogang, Muhammad Wannous","doi":"10.1109/ICASI.2018.8394556","DOIUrl":null,"url":null,"abstract":"The use of ICT has become essential to help farmers collect important and updated information and knowledge which are valuable resources that farming depends on. The study embarked investigates the problem sources of unavailability or lack of timely, relevant and accurate farming information and knowledge for small-scale farmers. The main target is to deal with plant diseases and how to manage them by carefully diagnosing the plants leaves. This work proposes to use image analysis and convolutional neural networks and the ever increasing capability of machine learning such as supervised learning to offer a mobile solution. A Design Science Research Methodology was followed in shaping skeleton of the proposed prototype. The developed prototype will be subjected to three usability measures to test if indeed it is timely, relevant and accurate as the farmers need it to be.","PeriodicalId":300510,"journal":{"name":"2018 IEEE International Conference on Applied System Invention (ICASI)","volume":"20 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2018-04-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"26","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2018 IEEE International Conference on Applied System Invention (ICASI)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICASI.2018.8394556","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 26
Abstract
The use of ICT has become essential to help farmers collect important and updated information and knowledge which are valuable resources that farming depends on. The study embarked investigates the problem sources of unavailability or lack of timely, relevant and accurate farming information and knowledge for small-scale farmers. The main target is to deal with plant diseases and how to manage them by carefully diagnosing the plants leaves. This work proposes to use image analysis and convolutional neural networks and the ever increasing capability of machine learning such as supervised learning to offer a mobile solution. A Design Science Research Methodology was followed in shaping skeleton of the proposed prototype. The developed prototype will be subjected to three usability measures to test if indeed it is timely, relevant and accurate as the farmers need it to be.