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.