This paper is published in Volume-6, Issue-3, 2020
Area
Computer Science and Engineering
Author
Rakshitha G., Yashaswini B. M., Sneha M., Shalini Singh A., Sonu C. S.
Org/Univ
Don Bosco Institute of Technology, Bangalore, Karnataka, India
Pub. Date
02 June, 2020
Paper ID
V6I3-1401
Publisher
Keywords
Support Vector Machine, Image Acquisition, Pre-Processng, Segmentation, Disease Detection

Citationsacebook

IEEE
Rakshitha G., Yashaswini B. M., Sneha M., Shalini Singh A., Sonu C. S.. Plant disease detection using Machine Learning, International Journal of Advance Research, Ideas and Innovations in Technology, www.IJARIIT.com.

APA
Rakshitha G., Yashaswini B. M., Sneha M., Shalini Singh A., Sonu C. S. (2020). Plant disease detection using Machine Learning. International Journal of Advance Research, Ideas and Innovations in Technology, 6(3) www.IJARIIT.com.

MLA
Rakshitha G., Yashaswini B. M., Sneha M., Shalini Singh A., Sonu C. S.. "Plant disease detection using Machine Learning." International Journal of Advance Research, Ideas and Innovations in Technology 6.3 (2020). www.IJARIIT.com.

Abstract

Agriculture is considered to be the backbone and major revenue producing of our country. Crops play an important role in our daily routine providing us with nourishments. Due to environmental conditions, crops are getting affected with many diseases. Farmers are not able to detect these diseases at an early stage. Thus, assessment of crop condition is vital. The growing technology plays a major role and techniques like Machine Learning, Deep Learning are used. Here in this project focuses on the assessment of the crop condition with the help of their leaves, Healthy as well as diseased leaves are capture using cameras from real-time environments, K-means clustering is used for segmentation. After segmentation undergo classification using Machine learning algorithms in which healthy and diseased leaves are detected.
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