Abstract: In this work designs and implements an intelligent AI-powered plant disease detection and classification system through Convolutional Neural Network. This study builds on a key limitation in ...
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 ...
According to a release from the Alabama Department of Agriculture and Industries, citrus canker has been detected in the county. ADAI will authorize a quarantine zone to be established. ADAI’s routine ...
1 Shandong Facility Horticulture Bioengineering Research Center, Weifang University of Science and Technology, Weifang, China 2 Department of Computer Engineering, Dongseo University, Busan, Republic ...
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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