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OpenAlex Citation Counts

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OpenAlex is a bibliographic catalogue of scientific papers, authors and institutions accessible in open access mode, named after the Library of Alexandria. It's citation coverage is excellent and I hope you will find utility in this listing of citing articles!

If you click the article title, you'll navigate to the article, as listed in CrossRef. If you click the Open Access links, you'll navigate to the "best Open Access location". Clicking the citation count will open this listing for that article. Lastly at the bottom of the page, you'll find basic pagination options.

Requested Article:

Multi-Modal Deep Learning for Weeds Detection in Wheat Field Based on RGB-D Images
Ke Xu, Yan Zhu, Weixing Cao, et al.
Frontiers in Plant Science (2021) Vol. 12
Open Access | Times Cited: 28

Showing 1-25 of 28 citing articles:

Applications of deep learning in precision weed management: A review
Nitin Rai, Yu Zhang, Billy G. Ram, et al.
Computers and Electronics in Agriculture (2023) Vol. 206, pp. 107698-107698
Open Access | Times Cited: 116
Plant image recognition with deep learning: A review
Huiling Chen, Yiqi Huang, Zizhao Zhang, et al.
Computers and Electronics in Agriculture (2023) Vol. 212, pp. 108072-108072
Closed Access | Times Cited: 53
Effective Multi-Species weed detection in complex wheat fields using Multi-Modal and Multi-View image fusion
Ke Xu, Qi Xie, Yan Zhu, et al.
Computers and Electronics in Agriculture (2025) Vol. 230, pp. 109924-109924
Closed Access | Times Cited: 2
Precision weed detection in wheat fields for agriculture 4.0: A survey of enabling technologies, methods, and research challenges
Ke Xu, Lei Shu, Qi Xie, et al.
Computers and Electronics in Agriculture (2023) Vol. 212, pp. 108106-108106
Closed Access | Times Cited: 32
Advances in ground robotic technologies for site-specific weed management in precision agriculture: A review
Arjun Upadhyay, Yu Zhang, Cengiz Koparan, et al.
Computers and Electronics in Agriculture (2024) Vol. 225, pp. 109363-109363
Open Access | Times Cited: 17
A review of vision-based crop row detection method: Focusing on field ground autonomous navigation operations
Shuo Zhang, Yü Liu, Kun Xiong, et al.
Computers and Electronics in Agriculture (2024) Vol. 222, pp. 109086-109086
Closed Access | Times Cited: 12
Weed detection and recognition in complex wheat fields based on an improved YOLOv7
Kaixin Wang, Xihong Hu, Huiwen Zheng, et al.
Frontiers in Plant Science (2024) Vol. 15
Open Access | Times Cited: 11
A New Training Strategy: Coordinating Distillation Techniques for Training Lightweight Weed Detection Model
Peng Zhou, Yifan Zhu, Chengqian Jin, et al.
Crop Protection (2025), pp. 107124-107124
Closed Access | Times Cited: 1
Application of Convolutional Neural Networks in Weed Detection and Identification: A Systematic Review.
Oscar Leonardo García-Navarrete, Adriana Corrêa-Guimarães, Luis Manuel Navas-Gracia
(2024)
Open Access | Times Cited: 8
Advancements and developments in the detection and control of invasive weeds: a global review of the current challenges and future opportunities
Jason Roberts, Singarayer Florentine
Weed Science (2024) Vol. 72, Iss. 3, pp. 205-215
Open Access | Times Cited: 7
Application of Convolutional Neural Networks in Weed Detection and Identification: A Systematic Review
Oscar Leonardo García-Navarrete, Adriana Corrêa-Guimarães, Luis Manuel Navas-Gracia
Agriculture (2024) Vol. 14, Iss. 4, pp. 568-568
Open Access | Times Cited: 7
Design of field real-time target spraying system based on improved YOLOv5
He Li, Changle Guo, Zishang Yang, et al.
Frontiers in Plant Science (2022) Vol. 13
Open Access | Times Cited: 24
A Review on the High-Efficiency Detection and Precision Positioning Technology Application of Agricultural Robots
Ruyi Wang, Linhong Chen, Zhike Huang, et al.
Processes (2024) Vol. 12, Iss. 9, pp. 1833-1833
Open Access | Times Cited: 5
Palmer amaranth identification using hyperspectral imaging and machine learning technologies in soybean field
Billy G. Ram, Yu Zhang, Cristiano André da Costa, et al.
Computers and Electronics in Agriculture (2023) Vol. 215, pp. 108444-108444
Closed Access | Times Cited: 10
Automated Grassweed Detection in Wheat Cropping System: Current Techniques and Future Scope
Swati Shrestha, Grishma Ojha, Gourav Sharma, et al.
Journal of precision agriculture. (2024) Vol. 1, Iss. 1, pp. 19-37
Open Access | Times Cited: 4
Review of weed recognition: A global agriculture perspective
Madeleine Darbyshire, Shaun R. Coutts, Petra Bosilj, et al.
Computers and Electronics in Agriculture (2024) Vol. 227, pp. 109499-109499
Open Access | Times Cited: 2
Multi-modal and multi-view image dataset for weeds detection in wheat field
Ke Xu, Zhijian Jiang, Qihang Liu, et al.
Frontiers in Plant Science (2022) Vol. 13
Open Access | Times Cited: 7
Detection of Mineral Deficiencies and Pests Symptoms in Coffee Crop Using Computer Vision
Sharad Timaji Tajane, B. Md. Irfan, C Sugunadevi, et al.
(2024), pp. 835-842
Closed Access | Times Cited: 1
Multi-layered CNN Architecture for Assistance in Smart Farming
G. L. N. Murthy, Baji Baba Shaik, CH. Bhargav Rami Reddy, et al.
2022 International Conference on Inventive Computation Technologies (ICICT) (2023), pp. 347-351
Closed Access | Times Cited: 1
Novel Approach for Crop Weed Detection in Wheat Fields Using Deep Learning Algorithms
Akanksha Bodhale, Seema Verma
Practice, progress, and proficiency in sustainability (2024), pp. 232-246
Closed Access
A Review on Crop and Weed Identification Using Deep Learning
Benakappa S M
INTERANTIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENT (2024) Vol. 08, Iss. 04, pp. 1-5
Open Access
Evaluation of Time-of-Flight Depth Cameras for Indoor Applications
Verônica Madeira Pacheco, T. M. Brown-Brandl, Raj Sharma, et al.
(2024)
Closed Access
Design of a disease identification system for wild jujube trees based on K210 and MobileNetV2
Yaqing Wei, Thelma D. Palaoag, Benny Zhang, et al.
(2024), pp. 159-163
Closed Access
Static laser weeding system based on improved YOLOv8 and image fusion
Xiwang Du, Xia Li, Fangtao Duan, et al.
Journal of Agricultural Engineering (2024)
Open Access
Effect of Depth Band Replacement on Red, Green and Blue Image for Deep Learning Weed Detection
Jan Vandrol, Janis Perren, Adrian Koller
Sensors (2024) Vol. 25, Iss. 1, pp. 161-161
Open Access
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