Weed detection to weed recognition: reviewing 50 years of research to identify constraints and opportunities for large-scale cropping systems
The past 50 yr of advances in weed recognition technologies have poised site-specific weed
control (SSWC) on the cusp of requisite performance for large-scale production systems …
control (SSWC) on the cusp of requisite performance for large-scale production systems …
Deep learning techniques for in-crop weed recognition in large-scale grain production systems: a review
Weeds are a significant threat to agricultural productivity and the environment. The
increasing demand for sustainable weed control practices has driven innovative …
increasing demand for sustainable weed control practices has driven innovative …
Performance of deep learning models for classifying and detecting common weeds in corn and soybean production systems
Knowing precise location and having accurate information about weed species is a
prerequisite for developing an effective site-specific weed management (SSWM) system …
prerequisite for developing an effective site-specific weed management (SSWM) system …
Weed detection in perennial ryegrass with deep learning convolutional neural network
Precision herbicide application can substantially reduce herbicide input and weed control
cost in turfgrass management systems. Intelligent spot-spraying system predominantly relies …
cost in turfgrass management systems. Intelligent spot-spraying system predominantly relies …
[HTML][HTML] Detection of fruit maturity stage and yield estimation in wild blueberry using deep learning convolutional neural networks
This study looked at the development of six deep learning artificial neural network models
for detecting ripeness stage in wild blueberries, along with developing models for yield …
for detecting ripeness stage in wild blueberries, along with developing models for yield …
Evaluation of different deep convolutional neural networks for detection of broadleaf weed seedlings in wheat
J Zhuang, X Li, M Bagavathiannan, X Jin… - Pest Management …, 2022 - Wiley Online Library
BACKGROUND In‐field weed detection in wheat (Triticum aestivum L.) is challenging due to
the occurrence of weeds in close proximity with the crop. The objective of this research was …
the occurrence of weeds in close proximity with the crop. The objective of this research was …
[HTML][HTML] Deep learning-based object detection system for identifying weeds using uas imagery
Current methods of broadcast herbicide application cause a negative environmental and
economic impact. Computer vision methods, specifically those related to object detection …
economic impact. Computer vision methods, specifically those related to object detection …
Goosegrass detection in strawberry and tomato using a convolutional neural network
Goosegrass is a problematic weed species in Florida vegetable plasticulture production. To
reduce costs associated with goosegrass control, a post-emergence precision applicator is …
reduce costs associated with goosegrass control, a post-emergence precision applicator is …
Deep convolutional neural network for large-scale date palm tree mapping from UAV-based images
Large-scale mapping of date palm trees is vital for their consistent monitoring and
sustainable management, considering their substantial commercial, environmental, and …
sustainable management, considering their substantial commercial, environmental, and …
Detection of weeds growing in Alfalfa using convolutional neural networks
J Yang, Y Wang, Y Chen, J Yu - Agronomy, 2022 - mdpi.com
Alfalfa (Medicago sativa L.) is used as a high-nutrient feed for animals. Weeds are a
significant challenge that affects alfalfa production. Although weeds are unevenly …
significant challenge that affects alfalfa production. Although weeds are unevenly …