Weed Management

Weed management research focuses on developing sustainable and precise methods to control weeds, minimizing herbicide use and its environmental impact while maximizing crop yields. Current efforts concentrate on developing autonomous robotic systems equipped with advanced computer vision, employing AI algorithms like YOLO and CNN architectures (including MobileNetV2) for real-time weed identification and targeted removal. These advancements leverage both supervised and semi-supervised learning techniques to improve accuracy and reduce the need for extensive labeled datasets. The resulting technologies offer significant potential for improving agricultural efficiency and sustainability.