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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:

Deep learning-based early weed segmentation using motion blurred UAV images of sorghum fields
Nikita Genze, Raymond Ajekwe, Zeynep Güreli, et al.
Computers and Electronics in Agriculture (2022) Vol. 202, pp. 107388-107388
Open Access | Times Cited: 42

Showing 1-25 of 42 citing articles:

Artificial Neural Networks in Agriculture, the core of artificial intelligence: What, When, and Why
Salvador Castillo‐Gironés, Sandra Munera, Marcelino Martı́nez-Sober, et al.
Computers and Electronics in Agriculture (2025) Vol. 230, pp. 109938-109938
Open Access | Times Cited: 1
Transforming weed management in sustainable agriculture with artificial intelligence: A systematic literature review towards weed identification and deep learning
Marios Vasileiou, Leonidas Sotirios Kyrgiakos, Christina Kleisiari, et al.
Crop Protection (2023) Vol. 176, pp. 106522-106522
Open Access | Times Cited: 36
Deep learning based weed detection and target spraying robot system at seedling stage of cotton field
Xiangpeng Fan, Xiujuan Chai, Jianping Zhou, et al.
Computers and Electronics in Agriculture (2023) Vol. 214, pp. 108317-108317
Closed Access | Times Cited: 33
Instance segmentation method for weed detection using UAV imagery in soybean fields
Beibei Xu, Jiahao Fan, Jun Chao, et al.
Computers and Electronics in Agriculture (2023) Vol. 211, pp. 107994-107994
Open Access | Times Cited: 31
Deep Learning-Based Weed Detection Using UAV Images: A Comparative Study
Tej Bahadur Shahi, Sweekar Dahal, Chiranjibi Sitaula, et al.
Drones (2023) Vol. 7, Iss. 10, pp. 624-624
Open Access | Times Cited: 22
WeedVision: A single-stage deep learning architecture to perform weed detection and segmentation using drone-acquired images
Nitin Rai, Xin Sun
Computers and Electronics in Agriculture (2024) Vol. 219, pp. 108792-108792
Open Access | Times Cited: 12
Rapid monitoring of tea plants under cold stress based on UAV multi-sensor data
Yilin Mao, He Li, Yu Wang, et al.
Computers and Electronics in Agriculture (2023) Vol. 213, pp. 108176-108176
Open Access | Times Cited: 19
Multi-level feature re-weighted fusion for the semantic segmentation of crops and weeds
Lamin L. Janneh, Yongjun Zhang, Zhongwei Cui, et al.
Journal of King Saud University - Computer and Information Sciences (2023) Vol. 35, Iss. 6, pp. 101545-101545
Open Access | Times Cited: 18
An automated weed identification framework for sugarcane crop: A deep learning approach
Rajesh U. Modi, Kancheti Mrunalini, A. Subeesh, et al.
Crop Protection (2023) Vol. 173, pp. 106360-106360
Closed Access | Times Cited: 17
Land-Cover Classification Using Deep Learning with High-Resolution Remote-Sensing Imagery
Muhammad Fayaz, Junyoung Nam, L. Minh Dang, et al.
Applied Sciences (2024) Vol. 14, Iss. 5, pp. 1844-1844
Open Access | Times Cited: 7
Monitoring of Antarctica’s Fragile Vegetation Using Drone-Based Remote Sensing, Multispectral Imagery and AI
Damini Raniga, A. Narmilan, Juan Sandino, et al.
Sensors (2024) Vol. 24, Iss. 4, pp. 1063-1063
Open Access | Times Cited: 5
Advancements of UAV and Deep Learning Technologies for Weed Management in Farmland
Jinmeng Zhang, Yu Feng, Qian Zhang, et al.
Agronomy (2024) Vol. 14, Iss. 3, pp. 494-494
Open Access | Times Cited: 5
Applications of Artificial Intelligence in sorghum and millet farming
Innocent Kutyauripo, Munyaradzi Charles Rushambwa, Rajkumar Palaniappan
Circular Agricultural Systems (2025) Vol. 5, Iss. 1
Open Access
Improved weed segmentation in UAV imagery of sorghum fields with a combined deblurring segmentation model
Nikita Genze, Maximilian Wirth, Christian Schreiner, et al.
Plant Methods (2023) Vol. 19, Iss. 1
Open Access | Times Cited: 13
Discovery of Novel Pyrazole Acyl Thiourea Skeleton Analogue as Potential Herbicide Candidates
Chujian Ma, Luyang Tian, Yan‐En Wang, et al.
Journal of Agricultural and Food Chemistry (2024) Vol. 72, Iss. 14, pp. 7727-7734
Closed Access | Times Cited: 4
A survey of unmanned aerial vehicles and deep learning in precision agriculture
Dashuai Wang, Minghu Zhao, Zhuolin Li, et al.
European Journal of Agronomy (2024) Vol. 164, pp. 127477-127477
Closed Access | Times Cited: 4
Intelligent weed management using aerial image processing and precision herbicide spraying: An overview
Armin Ehrampoosh, Pushpika Hettiarachchi, Anand Koirala, et al.
Crop Protection (2025), pp. 107206-107206
Open Access
Weed Detection from Unmanned Aerial Vehicle Imagery Using Deep Learning—A Comparison between High-End and Low-Cost Multispectral Sensors
Anna Teresa Seiche, Lucas Wittstruck, Thomas Jarmer
Sensors (2024) Vol. 24, Iss. 5, pp. 1544-1544
Open Access | Times Cited: 3
Automated detection of Crop-Row lines and measurement of maize width for boom spraying
Xinyue Zhang, Qingjie Wang, Xiuhong Wang, et al.
Computers and Electronics in Agriculture (2023) Vol. 215, pp. 108406-108406
Closed Access | Times Cited: 8
Manually annotated and curated Dataset of diverse Weed Species in Maize and Sorghum for Computer Vision
Nikita Genze, Wouter K. Vahl, Jennifer Groth, et al.
Scientific Data (2024) Vol. 11, Iss. 1
Open Access | Times Cited: 2
Artificial Intelligence and Smart Farming: An Overview
Varsha Kanojia, A. Subeesh, Nand Lal Kushwaha
Advances in geographical and environmental sciences (2024), pp. 3-22
Closed Access | Times Cited: 2
Weed Detection Algorithms in Rice Fields Based on Improved YOLOv10n
Yán Li, Zhonghui Guo, Yan Sun, et al.
Agriculture (2024) Vol. 14, Iss. 11, pp. 2066-2066
Open Access | Times Cited: 2
Artificial Intelligence Applied to Support Agronomic Decisions for the Automatic Aerial Analysis Images Captured by UAV: A Systematic Review
Josef Augusto Oberdan Souza Silva, Vilson Soares de Siqueira, Márcio Mesquita, et al.
Agronomy (2024) Vol. 14, Iss. 11, pp. 2697-2697
Open Access | Times Cited: 2
Quadcopters in Smart Agriculture: Applications and Modelling
Katia Karam, Ali Mansour, Mohamad R. Khaldi, et al.
Applied Sciences (2024) Vol. 14, Iss. 19, pp. 9132-9132
Open Access | Times Cited: 1
A review of unmanned aerial vehicle based remote sensing and machine learning for cotton crop growth monitoring
Nueraili Aierken, Bo Yang, Yongke Li, et al.
Computers and Electronics in Agriculture (2024) Vol. 227, pp. 109601-109601
Open Access | Times Cited: 1
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