Overview AI systems use sensors and computer vision to detect pests and diseases early, reducing crop damage and yield losses ...

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 ...

An artificial intelligence (AI) algorithm paired with the single-lead electrocardiogram (ECG) sensors on a smartwatch accurately diagnosed structural heart diseases, such as weakened pumping ability, ...

Introduction: Plant diseases pose a significant threat to global food security and agricultural productivity, making accurate and timely disease identification essential for effective crop management ...

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 ...

Abstract: Detection of plant leaf disease is crucial for achieving good yields and maintaining crop health. This early identification aids farmers who may not be familiar with all crop diseases by ...

This project provides a web interface for Plant Diseases Detection using Flask. It includes backend processing for model loading, image preprocessing, and predictions. The system also allows users to ...