首页    期刊浏览 2024年09月20日 星期五
登录注册

文章基本信息

  • 标题:Decision Support System Using CNN for Detecting the Type of Disease in Fruits and Vegetables
  • 本地全文:下载
  • 作者:A. Parkavi ; M.N. Pushpalatha ; Sini Anna Alex
  • 期刊名称:Webology
  • 印刷版ISSN:1735-188X
  • 出版年度:2022
  • 卷号:19
  • 期号:1
  • 页码:1315-1334
  • DOI:10.14704/WEB/V19I1/WEB19088
  • 语种:English
  • 出版社:University of Tehran
  • 摘要:The life of people in modern society is changing rapidly because of the high improvements in technology and tools, in the engineering sector. This evolution is also impacting the way of working of people in society in different domains. Machine Learning, Image Processing and Data Analytics are facilitating this growth but not much. Their rate of explorations and innovations in the field of Agriculture is very less, even though people know the importance of this sector and the rate of contribution to the GDP of the country. There are many reasons for it, such as the new generation has lost interest in agriculture as there is a lot of risk in agriculture due to improper irrigation methods, abnormal weather conditions, pests and diseases and finally lack of knowledge to handle the situations. But a country like India needs to focus more on innovations in the agriculture sector as it is the backbone of the country. In our work, we have made an attempt to analyze and find the different patterns of the disease appearing on the vegetable/fruit and identify the category of the disease. So, the prediction of disease type is done based on the patterns implemented using Convolutional Neural Network, and the accuracy of the models is measured. In this study, we have focused on tomato vegetable which is a major crop worldwide. This work can also make it flexible with other predominant fruits/vegetables to analyze it’s patterns and predict the relevant diseases.
  • 关键词:Decision Support System;Disease Detection;CNN;Fruits Disease Detection
国家哲学社会科学文献中心版权所有