Vol. 13, Issue 9 (2024)

Author(s):
Ranjeet Kumar

Abstract:
Weed management is a crucial aspect of agricultural productivity and sustainability. Traditional weeding techniques, such as manual labor and chemical herbicide application, pose economic and environmental challenges. Recent advancements in artificial intelligence (AI), machine learning (ML), and computer vision have enabled the development of automatic weed detection systems, improving precision and efficiency. This paper reviews the current methodologies used in automatic weed detection, including image processing, deep learning techniques, and robotic weed control. The paper also discusses challenges and future research directions in the field.