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Stream/Area:
-
Subject:
-
Paper ID:
IJSREM46720
Volume:
9 |
5 |
May 2025
Pages:
Publication Frequency:
Monthly (12 issues per year)
License:International Journal of Scientific Research in Engineering and Management follows the Creative Commons Attribution 4.0 (CC BY 4.0) License, allowing free use and distribution with proper attribution.
Diseased images can severely reduce agricultural productivity and harm a nationâs food supply. Typically, farmers and specialists closely monitor the diseases. It  can be labor-intensive, costly, and ineffective. Detecting plant diseases can be achieved by affected leaves. The approach for detecting plant diseases by building a classification model that analyzes leaf images. To identify plant diseases, we utilize image processing alongside a (CNN). CNNs are a class of models capable of takes features from images, make an ideal for recognizing disease patterns in plant leaves.
KEYWORDS
Publication Date
5/2/2025
Peer Review Type
Double-Blind Peer Review
Review Rounds: 2
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Conflict of Interest
The authors declare no conflict of interest related to this research work.
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