Plant pesticide recommender application for remote villages using convolution neural network
Department of Information Technology, Bharathiar University, Coimbatore-641 046, Tamil Nadu, India.
Research Article
World Journal of Advanced Research and Reviews, 2023, 18(01), 511–519
Article DOI: 10.30574/wjarr.2023.18.1.0592
Publication history:
Received on 27 February 2023; revised on 09 April 2023; accepted on 11 April 2023
Abstract:
One of the primary issues with inside the agricultural region is crop sicknesses and automated detection is crucial for crop monitoring. Plant leaves generally display the maximum ailment symptoms, however professional laboratory leaf analysis is high priced and time-consuming. According to the Food and Agriculture Organization (FAO), agricultural pests lessen crop yields international via way of means of 20 to 40% according to year. Smart farming is good solution for farmers is to apply artificial intelligence techniques along with modern statistics and communication technologies to get rid of those dangerous insect infestations. Farmers can substantially lessen financial losses via way of means of treating plants directly and detecting sicknesses and pests in apple, mango and graphs leaves appropriately and timely. Image type accuracy has progressed notably because of latest advances in deep studying-primarily based totally convolutional neural networks (CNN). This article evolved strategies primarily based totally on deep studying to hit upon sicknesses and pests in apples, mango, and grape leaves. These strategies have been influenced via way of means of the achievement of CNNs in photograph type.
Keywords:
Artificial Intelligence; Deep Convolutional Neural Networks; Leaf diseases identification Machine learning Machine learning; Image processing; Pest Detection
Full text article in PDF:
Copyright information:
Copyright © 2023 Author(s) retain the copyright of this article. This article is published under the terms of the Creative Commons Attribution Liscense 4.0