This paper is published in Volume-6, Issue-4, 2020
Area
Information Science
Author
Harshith P. K., Bitopan Deka, Nikhil N., Sumanth T. S.
Org/Univ
Sai Vidya Institute of Technology, Bengaluru, Karnataka, India
Pub. Date
18 August, 2020
Paper ID
V6I4-1396
Publisher
Keywords
Machine Learning, Models, Plant Diseases

Citationsacebook

IEEE
Harshith P. K., Bitopan Deka, Nikhil N., Sumanth T. S.. Accuracy of Machine Learning Models for Plant Disease Detection, International Journal of Advance Research, Ideas and Innovations in Technology, www.IJARIIT.com.

APA
Harshith P. K., Bitopan Deka, Nikhil N., Sumanth T. S. (2020). Accuracy of Machine Learning Models for Plant Disease Detection. International Journal of Advance Research, Ideas and Innovations in Technology, 6(4) www.IJARIIT.com.

MLA
Harshith P. K., Bitopan Deka, Nikhil N., Sumanth T. S.. "Accuracy of Machine Learning Models for Plant Disease Detection." International Journal of Advance Research, Ideas and Innovations in Technology 6.4 (2020). www.IJARIIT.com.

Abstract

Agriculture is the backbone of a nation. India has about 96 million hectare of irrigated land. With the amount of land that is cultivated as farmland, detection and prevention of diseases in crops is paramount. When diseases affect plants, particularly through their leaves it effects the production of agricultural produce and decreases profitability of a given crop. Timely identification of these diseases is very challenging in affected plants. A reliable and fast way for the detection of diseases is necessary. Detecting disease may be a key to stop agricultural losses. The aim of this is to develop a software system that is able to efficiently find and classify diseases occurring in plants. The pictures of leaves can be used for detecting the plant diseases. Therefore, use of image process technique to find and classify diseases in agricultural applications is useful.
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