Plant Disease Detection using CNN

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.

Plant phenotyping relevance

植物の葉画像から健全・罹病状態を推定するCNN手法の開発が研究の中心であり、病害状態の画像ベースフェノタイピングに該当する。

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