The PlantIF framework consists of image and text feature extractors, semantic space encoders, and a multimodal feature fusion module. Image and text feature extractors are used to present visual and ...
This project uses deep learning to automatically detect plant diseases from leaf images. The model leverages Convolutional Neural Networks (CNNs) and Transfer Learning (MobileNetV2) for accurate and ...
In general, disease refers to an illness of living organisms caused by either infection or health failure rather than an accident. Specifically, Encyclopedia of Microbiology (Third Edition) 2009 has ...
The growing global population and rising concerns about food security highlight the critical need for intelligent agriculture. Among various technologies, plant disease detection is vital but faces ...
Abstract: Global food security is seriously threatened by plant diseases, especially in areas with limited access to prompt professional diagnosis. We introduce PlantNet, a deep learning-powered ...
This project aims to develop a method for detecting plant diseases using CNNs by analyzing leaf images.The CNNs are proficient in handling large datasets and can dynamically learn new features from ...
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: 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 ...
Some results have been hidden because they may be inaccessible to you
Show inaccessible results