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 ...

Plant diseases cause an estimated 30% annual crop yield loss worldwide, resulting in hundreds of billions of dollars in economic damage and increasingly threatening native and ornamental plants ...

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 ...

As climate change alters the frequency, intensity, and co-occurrences of abiotic and biotic stresses, the effective and efficient detection of plant stress responses and resistance mechanisms 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 comprehensive deep learning project for plant disease classification using state-of-the-art CNN architectures. This project implements multiple models to detect diseases in different plant species ...

You walk into the bay and notice some plants looking wilted. The irrigation system is working, so what’s going on? Is it drought stress, or is a disease problem starting to develop? Unfortunately, ...