Plant Disease Detection using CNN

S, Shivasangari

doi:https://doi.org/10.55041/ijsmt.v2i3.305

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PLANT DISEASE DETECTION USING CNN

AUTHORS:

Shivasangari S

Mentor

I.Ajitha

Affiliation

Department of CT Dr.N.G.P Arts and Science College Coimbatore

DOI: 10.55041/ijsmt.v2i3.305

CC BY 4.0 License:

This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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Abstract

Agriculture plays a significant role in the economic development of many countries. Plant diseases severely affect crop productivity and quality, leading to economic loss for farmers. Early and accurate disease detection is essential to improve yield and ensure food security. This paper proposes a deep learning-based plant disease detection system using Convolutional Neural Network (CNN). The system classifies leaf images into healthy and diseased categories. The proposed model performs image preprocessing, feature extraction, and classification to provide accurate predictions. Experimental results show that the model achieves high accuracy across multiple plant species. The system can be deployed as a web-based application for real-time disease prediction.

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✓ All ethical standards met

This article has undergone plagiarism screening and double-blind peer review. Editorial policies have been followed. Authors retain copyright under CC BY-NC 4.0 license. The research complies with ethical standards and institutional guidelines.

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