Accurate detection of crop diseases from unmanned aerial vehicle (UAV) imagery is critical for precision agriculture. This task remains challenging due to the complex backgrounds, variable scales of ...

A full-stack web application that uses deep learning to detect and classify plant diseases from leaf images. Built with Next.js, React, TailwindCSS on the frontend and Flask, TensorFlow on the backend ...

This study proposes EDGE-MSE-YOLOv11, a novel lightweight rice disease detection model based on a unified Tri-Module Lightweight Perception Mechanism (TMLPM). This mechanism integrates three core ...

Abstract: This study focuses on the early and accurate detection of tomato plant diseases using the lightweight and efficient deep learning model YOLOv11n. Early identification of plant diseases is ...

ABSTRACT: Timely and accurate detection of plant diseases is essential for improving crop yields and ensuring food security, particularly in regions like Cameroon, where farmers often rely on visual ...

1 Ambam Computer Science and Application Laboratory & Department of Computer Engineering, Higher Institute of Transport, Logistics and Commerce, University of Ebolowa, Ebolowa, Cameroon. 2 Institut ...

A web-based application that uses deep learning to detect plant diseases from leaf images. The system can identify 15 different plant diseases across multiple crops including Apple, Cherry, Corn, ...