4.7 Review

Key technologies of machine vision for weeding robots: A review and benchmark

Related references

Note: Only part of the references are listed.
Review Remote Sensing

An open source workflow for weed mapping in native grassland using unmanned aerial vehicle: usingRumex obtusifoliusas a case study

Olee Hoi Ying Lam et al.

Summary: A proposed open-source workflow utilized a commercially available UAV for automated weed mapping in a nature reserve, achieving high accuracy and F1 scores in early weed detection. This method showed potential for semi- or fully automated early weed detection system in grasslands using UAV-imagery.

EUROPEAN JOURNAL OF REMOTE SENSING (2021)

Review Agriculture, Multidisciplinary

A survey of deep learning techniques for weed detection from images

A. S. M. Mahmudul Hasan et al.

Summary: The rapid development of deep learning techniques has enabled efficient detection and classification of objects from images or videos, with applications in agriculture especially for weed management. Automated weed detection plays a key role in improving crop yields and fine-tuning pre-trained models on plant datasets has proven to achieve high accuracy.

COMPUTERS AND ELECTRONICS IN AGRICULTURE (2021)

Review Agriculture, Multidisciplinary

Drone and sensor technology for sustainable weed management: a review

Marco Esposito et al.

Summary: Weeds are a significant abiotic factor impacting agriculture globally, causing important yield loss. Integrated Weed Management with the use of drones enables efficient and environmentally beneficial Site-Specific Weed Management. The identification of weed patches through drone image acquisition and machine learning techniques can lead to the training of specific algorithms for weed removal by Autonomous Weeding Robots.

CHEMICAL AND BIOLOGICAL TECHNOLOGIES IN AGRICULTURE (2021)

Review Agronomy

Using Remote Sensing and an Unmanned Aerial System for Weed Management in Agricultural Crops: A Review

Muhammad Huzaifah Mohd Roslim et al.

Summary: Weeds are unwanted plants that reduce crop yields and need to be controlled; integrating technologies like drones can better manage weed problems; future challenges can be overcome through remote sensing and machine learning approaches.

AGRONOMY-BASEL (2021)

Article Computer Science, Information Systems

Weed Identification Using Deep Learning and Image Processing in Vegetable Plantation

Xiaojun Jin et al.

Summary: This paper presents a new method for ground-based weed identification in vegetable plantation, combining deep learning and image processing technology with a trained CenterNet model. By utilizing color index and image segmentation techniques, high-quality weed identification was achieved, providing a new solution for agricultural production.

IEEE ACCESS (2021)

Article Computer Science, Artificial Intelligence

Focal Loss for Dense Object Detection

Tsung-Yi Lin et al.

IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE (2020)

Article Agriculture, Multidisciplinary

Towards weeds identification assistance through transfer learning

Borja Espejo-Garcia et al.

COMPUTERS AND ELECTRONICS IN AGRICULTURE (2020)

Article Agriculture, Multidisciplinary

Graph weeds net: A graph-based deep learning method for weed recognition

Kun Hu et al.

COMPUTERS AND ELECTRONICS IN AGRICULTURE (2020)

Article Agriculture, Multidisciplinary

CNN feature based graph convolutional network for weed and crop recognition in smart farming

Honghua Jiang et al.

COMPUTERS AND ELECTRONICS IN AGRICULTURE (2020)

Article Plant Sciences

Instance segmentation for the fine detection of crop and weed plants by precision agricultural robots

Julien Champ et al.

APPLICATIONS IN PLANT SCIENCES (2020)

Article Multidisciplinary Sciences

Dataset of annotated food crops and weed images for robotic computer vision control

Kaspars Sudars et al.

DATA IN BRIEF (2020)

Review Agriculture, Multidisciplinary

A review on weed detection using ground-based machine vision and image processing techniques

Aichen Wang et al.

COMPUTERS AND ELECTRONICS IN AGRICULTURE (2019)

Article Agronomy

Deep learning for image-based weed detection in turfgrass

Jialin Yu et al.

EUROPEAN JOURNAL OF AGRONOMY (2019)

Article Multidisciplinary Sciences

DeepWeeds: A Multiclass Weed Species Image Dataset for Deep Learning

Alex Olsen et al.

SCIENTIFIC REPORTS (2019)

Review Computer Science, Information Systems

A Review on UAV-Based Applications for Precision Agriculture

Dimosthenis C. Tsouros et al.

INFORMATION (2019)

Article Computer Science, Artificial Intelligence

Weed Management of the Future

Sandra Amend et al.

KUNSTLICHE INTELLIGENZ (2019)

Article Agricultural Engineering

On-line crop/weed discrimination through the Mahalanobis distance from images in maize fields

Ivan D. Garcia-Santillan et al.

BIOSYSTEMS ENGINEERING (2018)

Article Computer Science, Interdisciplinary Applications

Visual features based boosted classification of weeds for real-time selective herbicide sprayer systems

Jamil Ahmad et al.

COMPUTERS IN INDUSTRY (2018)

Article Computer Science, Interdisciplinary Applications

A fast and accurate expert system for weed identification in potato crops using metaheuristic algorithms

Sajad Sabzi et al.

COMPUTERS IN INDUSTRY (2018)

Article Chemistry, Analytical

Weed Growth Stage Estimator Using Deep Convolutional Neural Networks

Nima Teimouri et al.

SENSORS (2018)

Article Agriculture, Multidisciplinary

Robotic in-row weed control in vegetables

Trygve Utstumo et al.

COMPUTERS AND ELECTRONICS IN AGRICULTURE (2018)

Article Agriculture, Multidisciplinary

Improving efficiency of organic farming by using a deep learning classification approach

Florian J. Knoll et al.

COMPUTERS AND ELECTRONICS IN AGRICULTURE (2018)

Proceedings Paper Energy & Fuels

Space Charge Analysis of Polyethylene with Chemical Defects Based on Density Function Theory

Tao Lin et al.

2018 IEEE INTERNATIONAL CONFERENCE ON HIGH VOLTAGE ENGINEERING AND APPLICATION (ICHVE) (2018)

Article Agronomy

UAV Low-Altitude Remote Sensing for Precision Weed Management

Yanbo Huang et al.

WEED TECHNOLOGY (2018)

Article Robotics

weedNet: Dense Semantic Weed Classification Using Multispectral Images and MAV for Smart Farming

Inkyu Sa et al.

IEEE ROBOTICS AND AUTOMATION LETTERS (2018)

Article Computer Science, Artificial Intelligence

Faster R-CNN: Towards Real-Time Object Detection with Region Proposal Networks

Shaoqing Ren et al.

IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE (2017)

Article Robotics

Agricultural robot dataset for plant classification, localization and mapping on sugar beet fields

Nived Chebrolu et al.

INTERNATIONAL JOURNAL OF ROBOTICS RESEARCH (2017)

Article Robotics

Robot for weed species plant-specific management

Owen Bawden et al.

JOURNAL OF FIELD ROBOTICS (2017)

Article Agriculture, Multidisciplinary

Weed identification based on K-means feature learning combined with convolutional neural network

JingLei Tang et al.

COMPUTERS AND ELECTRONICS IN AGRICULTURE (2017)

Proceedings Paper Computer Science, Information Systems

Weed Detection Dataset with RGB Images Taken Under Variable Light Conditions

Petre Lameski et al.

ICT INNOVATIONS 2017: DATA-DRIVEN INNOVATION (2017)

Article Agriculture, Multidisciplinary

Early season weed mapping in sunflower using UAV technology: variability of herbicide treatment maps against weed thresholds

Francisca Lopez-Granados et al.

PRECISION AGRICULTURE (2016)

Review Agriculture, Multidisciplinary

A survey of image processing techniques for plant extraction and segmentation in the field

Esmael Hamuda et al.

COMPUTERS AND ELECTRONICS IN AGRICULTURE (2016)

Proceedings Paper Computer Science, Artificial Intelligence

A Crop/Weed Field Image Dataset for the Evaluation of Computer Vision Based Precision Agriculture Tasks

Sebastian Haug et al.

COMPUTER VISION - ECCV 2014 WORKSHOPS, PT IV (2015)

Proceedings Paper Computer Science, Artificial Intelligence

Fast R-CNN

Ross Girshick

2015 IEEE INTERNATIONAL CONFERENCE ON COMPUTER VISION (ICCV) (2015)

Article Agricultural Engineering

Vegetation segmentation robust to illumination variations based on clustering and morphology modelling

Xiaodong Bai et al.

BIOSYSTEMS ENGINEERING (2014)

Review Agriculture, Multidisciplinary

Autonomous robotic weed control systems: A review

D. C. Slaughter et al.

COMPUTERS AND ELECTRONICS IN AGRICULTURE (2008)

Article Agriculture, Multidisciplinary

Determination of crop rows by image analysis without segmentation

HT Sogaard et al.

COMPUTERS AND ELECTRONICS IN AGRICULTURE (2003)

Article Agricultural Engineering

Robotic weed control using machine vision

J Blasco et al.

BIOSYSTEMS ENGINEERING (2002)

Article Computer Science, Artificial Intelligence

An agricultural mobile robot with vision-based perception for mechanical weed control

B Åstrand et al.

AUTONOMOUS ROBOTS (2002)