Abstract: Agricultural productivity is something on which economy exceptionally depends. This is the one reason that disease detection in plants plays an important part in agriculture field, as having disease in plants are very natural. If proper care isn't taken here then it causes genuine consequences for plants and because of which respective product quality, quantity or productivity is affected. Detection of plant disease through some automated system is valuable as it reduces an extensive work of monitoring in huge farms of crops, and at beginning period itself it detects the symptoms of diseases i.e. when they show up on plant leaves.In this paper, we propose a novel frameworkto recognize plant leaf disease in combination of K-means clustering and Neural Network Algorithm. The proposed technique successfully identify and classify the infected plant leaves.
Keywords: Feature Extraction, Dicot Plant Disease, Monocot Plant Disease, Pre-Processing, Segmentation, Classifier.
Title: Machine Learning Based Segmentation Technique of Detection of Fungal Diseases in Plants
Author: Roshni gupta, AP. Mr. Ankit Arora
International Journal of Interdisciplinary Research and Innovations
ISSN 2348-1218 (print), ISSN 2348-1226 (online)
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