Earnings announcements are one of the few scheduled events that consistently move markets. Prices react not just to the reported numbers, but to how those numbers compare with expectations. A small ...
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 ...
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 ...
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 ...
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 ...
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