Automated Detection of Plant Diseases Using CNN

Abstract

Abstract—Diseased images can severely reduce agricultural productivity and harm a nation's 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—CNN, image processing, training set, test set

Code and data availability

The paper uses the public PlantVillage dataset, but that is a pre-existing external dataset (cited prior work), not a paper-specific deposit. No author code, trained model checkpoints, or data availability statements with URLs are provided, and no allowed URLs exist to cite.

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