Studies on Detecting Plant Leaf Disease Using KNN Classifier and Severity Measurement
Food is one of the most basic needs of living beings. It is very essential to grow a sufficient quantity of crops to cope with the growing population. With time, it is seen that plants are being affected by various kinds of diseases. Different plant diseases are a major influence on agricultural output limitations, and they are generally difficult to control. As a result, early detection of plant diseases is crucial for avoiding output losses and improving the quality of agricultural goods. This research paper proposes a method to detect and classify the disease on plant leaves with a severity measurement for the grading system. The paper describes a machine learning-based detection and classification of diseases like early blight and late blight on "potato leaf" using the KNN classifier. Our research focuses on a rigorous examination of potato plant disease segmentation approaches.
Authors
- M Madhushree
- V Akshaya
- S. Pravinth Raja
- M. Sinthuja
Institutions
- Presidency University (IN)
- M S Ramaiah University of Applied Sciences (IN)
- Sri Ramakrishna Institute of Paramedical Sciences (IN)
- Presidency University (BD)
- M S Ramaiah Memorial Hospital (IN)
Publication Details
- Journal
- Journal of Mines Metals and Fuels
- Published
- 2024-12-20
- DOI
- https://doi.org/10.18311/jmmf/2023/47275
- Primary Topic
- Smart Agriculture and AI
- Type
- article
- Field-Weighted Citation Impact
- 0.00