Leaf Doctor: An Advanced Plant Disease Detection Web Application

Abstract

Leaf Doctor is an advanced plant disease detection web application that assists farmers and agricultural researchers in diagnosing plant diseases through image analysis. Using machine learning algorithms, the system analyzes leaf images to identify signs of disease, providing users with accurate and timely insights. The platform enhances agricultural efficiency by offering real-time disease detection, reducing crop loss, and promoting sustainable farming practices. As a cloud-based solution, Leaf Doctor is accessible from multiple devices, ensuring widespread usability for farmers and agronomists. Key Words: Plant Disease Detection, Gated Recurrent Unit, Leaf Image Analysis, Streamlit, Real Time Diagnosis, Sustainable Farming.

Plant phenotyping relevance

葉画像から植物病徴を機械学習で検出するWebアプリケーションが研究の中心であり、植物の病害状態を観測・推定するフェノタイピング手法に該当する。

Code and data availability

The paper's plant disease detection model is trained on a public Kaggle leaf image dataset (New Plant Diseases Dataset, ~87,000 labeled RGB leaf images, 38 classes), which is a paper-specific, publicly available phenotyping image asset with an authors' URL in the references. No author analysis code or trained model is公