In the face of increasing agricultural demands and environmental concerns, the effective
management of weeds presents a pressing challenge in modern agriculture. Weeds not only …

Abstract Machine learning and deep learning are subsets of Artificial Intelligence that have
revolutionized object detection and classification in images or videos. This technology plays …

Weeds are unwanted plants on agricultural soil. They always competing for sunlight,
nutrient, space and water with economic crops. Uncontrolled weed growth can cause both …

Traditional means of weed removal, such as human work or the use of pesticides, frequently
require significant amounts of effort, incur high expenses, and can negatively impact the …

Precision weed management (PWM), driven by machine vision and deep learning (DL)
advancements, not only enhances agricultural product quality and optimizes crop yield but …

Precision agriculture relies on effective weed management for high yields and crop quality.
Deep learning (DL)-based techniques show potential for providing effective solutions …

Detecting weeds at an early stage is crucial in reducing herbicide usage and preventing
significant losses in agricultural productivity. The emergence of new computer vision …

The implementation of a machine-vision system for real-time precision weed management is
a crucial step towards the development of smart spraying robotic vehicles. The intelligent …

Since farming is becoming increasingly more expensive, efficient farming entails doing so
without suffering any losses, which is what the current situation desires. Weeds are a key …

Recent years have seen the emergence of various precision weed management
technologies in both research and commercial contexts. These technologies better target …