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Xiaojun Jin et al.
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Petra Bosilj et al.
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Joseph E. Hunter et al.
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Junfeng Gao et al.
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Borja Espejo-Garcia et al.
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Hyunseok Seo et al.
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Kun Hu et al.
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Julien Champ et al.
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Kaspars Sudars et al.
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Aichen Wang et al.
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A review on weed detection using ground-based machine vision and image processing techniques
Aichen Wang et al.
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Jialin Yu et al.
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Yu Jiang et al.
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Dimosthenis C. Tsouros et al.
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Nan Li et al.
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Sandra Amend et al.
KUNSTLICHE INTELLIGENZ (2019)
On-line crop/weed discrimination through the Mahalanobis distance from images in maize fields
Ivan D. Garcia-Santillan et al.
BIOSYSTEMS ENGINEERING (2018)
Visual features based boosted classification of weeds for real-time selective herbicide sprayer systems
Jamil Ahmad et al.
COMPUTERS IN INDUSTRY (2018)
A fast and accurate expert system for weed identification in potato crops using metaheuristic algorithms
Sajad Sabzi et al.
COMPUTERS IN INDUSTRY (2018)
Weed Growth Stage Estimator Using Deep Convolutional Neural Networks
Nima Teimouri et al.
SENSORS (2018)
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Trygve Utstumo et al.
COMPUTERS AND ELECTRONICS IN AGRICULTURE (2018)
Improving efficiency of organic farming by using a deep learning classification approach
Florian J. Knoll et al.
COMPUTERS AND ELECTRONICS IN AGRICULTURE (2018)
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Philipp Lottes et al.
IEEE ROBOTICS AND AUTOMATION LETTERS (2018)
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Tao Lin et al.
2018 IEEE INTERNATIONAL CONFERENCE ON HIGH VOLTAGE ENGINEERING AND APPLICATION (ICHVE) (2018)
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Yanbo Huang et al.
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Inkyu Sa et al.
IEEE ROBOTICS AND AUTOMATION LETTERS (2018)
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Philipp Lottes et al.
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Faster R-CNN: Towards Real-Time Object Detection with Region Proposal Networks
Shaoqing Ren et al.
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Agricultural robot dataset for plant classification, localization and mapping on sugar beet fields
Nived Chebrolu et al.
INTERNATIONAL JOURNAL OF ROBOTICS RESEARCH (2017)
Robot for weed species plant-specific management
Owen Bawden et al.
JOURNAL OF FIELD ROBOTICS (2017)
Weed identification based on K-means feature learning combined with convolutional neural network
JingLei Tang et al.
COMPUTERS AND ELECTRONICS IN AGRICULTURE (2017)
Weed Detection Dataset with RGB Images Taken Under Variable Light Conditions
Petre Lameski et al.
ICT INNOVATIONS 2017: DATA-DRIVEN INNOVATION (2017)
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)
A survey of image processing techniques for plant extraction and segmentation in the field
Esmael Hamuda et al.
COMPUTERS AND ELECTRONICS IN AGRICULTURE (2016)
Study and comparison of color models for automatic image analysis in irrigation management applications
G. Garcia-Mateos et al.
AGRICULTURAL WATER MANAGEMENT (2015)
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)
Fast R-CNN
Ross Girshick
2015 IEEE INTERNATIONAL CONFERENCE ON COMPUTER VISION (ICCV) (2015)
Vegetation segmentation robust to illumination variations based on clustering and morphology modelling
Xiaodong Bai et al.
BIOSYSTEMS ENGINEERING (2014)
Classification of crops and weeds from digital images: A support vector machine approach
Faisal Ahmed et al.
CROP PROTECTION (2012)
Autonomous robotic weed control systems: A review
D. C. Slaughter et al.
COMPUTERS AND ELECTRONICS IN AGRICULTURE (2008)
Determination of crop rows by image analysis without segmentation
HT Sogaard et al.
COMPUTERS AND ELECTRONICS IN AGRICULTURE (2003)
Robotic weed control using machine vision
J Blasco et al.
BIOSYSTEMS ENGINEERING (2002)
An agricultural mobile robot with vision-based perception for mechanical weed control
B Åstrand et al.
AUTONOMOUS ROBOTS (2002)