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 …

Precision spraying can significantly reduce herbicide input for turf weed management. A
major challenge for autonomous precision herbicide spraying is to accurately and reliably …

The advancement of computer vision technology has allowed for the easy detection of
weeds and other stressors in turfgrasses and agriculture. This study aimed to evaluate the …

BACKGROUND Accurate detection of weeds and estimation of their coverage is crucial for
implementing precision herbicide applications. Deep learning (DL) techniques are typically …

Abstract Machine vision-based precision herbicide application in wheat (Triticum aestivum
L.) can substantially reduce herbicide input. However, detecting newly emerged weeds in …

Precision herbicide application can substantially reduce herbicide input, thereby cutting
chemical costs and minimizing adverse environmental impacts. A smart sprayer prototype …

Precision application of specific herbicides to susceptible weeds can significantly save
herbicide. This is the first study evaluating the performances of precision sprayer for weed …

Drones are being used for agriculture monitoring in many different crops. Nevertheless, the
use of drones for green areas' evaluation is limited, and information is scattered. In this …

Pesticides are extensively used agrochemicals across the world to control pest populations.
However, irrational application of pesticides leads to contamination of various components …

Deep learning-based methods for weed detection and precise herbicide application are
promising for reducing herbicide input and weed control costs. However, training the neural …