Plant Leaf Disease Detection Using Deep Learning

Abstract

Agriculture is the backbone of food security and a primary source of income for many nations. However, plant diseases caused by fungi, bacteria, and viruses lead to significant crop losses, making early detection and timely treatment essential. In this project, we propose a leaf disease detection system that utilizes computer vision and deep learning (CNNs) to analyze plant leaf images and accurately identify diseases. Once detected, the system provides detailed disease information, recommended pesticides, and preventive measures. A unique feature of this system is its voice-enabled advisory service, where the AI automatically generates speech and calls the farmer in their local language to explain the disease status and suggest remedies. This approach ensures accessibility for farmers with limited literacy, while enabling quick, effective, and informed decision-making. By combining deep learning accuracy with AIpowered voice interaction, the system aims to reduce crop loss and enhance agricultural productivity.

Code and data availability

植物フェノタイピング解析を再現する公開資産であることを、入力本文と直接リンクから確認できなかったため保留しました。

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