Abstract:
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Corresponding author email : bouacidaimane1@gmail.com
Leveraging YOLOv9 in Agriculture: An Intelligent System for
Efficient Weed Detection
Bouacida, Imane*
8 mai 1945 Guelma University
Abstract
This research focuses on weed detection using artificial intelligence (AI) in
agriculture. The goal of the study is to develop an intelligent system capable of
automatically detecting and classifying weeds in agricultural fields through
image analysis. Traditional manual weed detection methods are time-
consuming, costly, and prone to human error. By harnessing advances in
machine learning, image processing, and deep learning, an AI-based system can
provide accurate, real-time information on weed presence, enabling farmers to
optimize agricultural production
