Image Based Plant Disease Detection using CNN: An Experimental Research

Journal: GRENZE International Journal of Engineering and Technology
Authors: Disha Wankhede, Aman Narnaware, Abhaykumar Baral, Akash Gawade, Atharva Valsange
Volume: 10 Issue: 2
Grenze ID: 01.GIJET.10.2.529 Pages: 178-185

Abstract

The first step in preventing losses in agricultural product output and quantity is the identification of plant diseases. The study of patterns that are visible to the human eye on plants is referred to as plant disease research. Plant disease identification and health monitoring are essential for sustainable agriculture. Manually keeping an eye on plant diseases is really challenging. It necessitates an enormous amount of processing time, a great deal of labor, and knowledge of plant diseases. Therefore, plant disease detection uses image processing. A number of processes are involved in disease detection, including feature extraction, classification, segmentation, pre-processing, and image acquisition. This study examined techniques for identifying plant illnesses using photos of their leaves. A few segmentation and feature extraction techniques for plant disease identification were also covered in this work.

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