Abstract Purpose of Review The goal of this review is to provide an overview of current
robotic approaches to precision weed management. This includes an investigation into …

This paper provides an overview of the recent developments in remote sensing technology
and machine learning algorithms for estimating important biophysical and biochemical …

This paper explores the potential of machine learning algorithms for weed and crop
classification from UAV images. The identification of weeds in crops is a challenging task …

This study aimed to compare and assess different Geographic Object-Based Image Analysis
(GEOBIA) and machine learning algorithms using unmanned aerial vehicles (UAVs) …

Weeds are among the most harmful abiotic factors in agriculture, triggering significant yield
loss worldwide. Remote sensing can detect and map the presence of weeds in various …

Currently, applying uniform distribution of chemical herbicide through a sprayer without
considering the spatial distribution information of crops and weeds is the most common …

In this study, we propose a method for discriminating crops/weeds in upland rice fields using
a commercial unmanned aerial vehicles (UAVs) and red-green-blue (RGB) cameras with the …

Given the importance of olive growing, especially in Mediterranean countries, it is crucial
that there is a constant process of modernization aimed at both environmental sustainability …

Accurate and timely weed mapping between and within trees is considered one of the major
challenges in the site-specific weed management systems. This research presents the first …

The development of UAV (unmanned aerial vehicle) imaging technologies for precision
farming applications is rapid, and new studies are published frequently. In cases where …