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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:

A novel deep learning‐based method for detection of weeds in vegetables
Xiaojun Jin, Yanxia Sun, Jun Che, et al.
Pest Management Science (2022) Vol. 78, Iss. 5, pp. 1861-1869
Closed Access | Times Cited: 92

Showing 1-25 of 92 citing articles:

A survey of few-shot learning in smart agriculture: developments, applications, and challenges
Jiachen Yang, Xiaolan Guo, Yang Li, et al.
Plant Methods (2022) Vol. 18, Iss. 1
Open Access | Times Cited: 104
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: 46
Deep Learning-Based Weed–Crop Recognition for Smart Agricultural Equipment: A Review
Hao-Ran Qu, Wen‐Hao Su
Agronomy (2024) Vol. 14, Iss. 2, pp. 363-363
Open Access | Times Cited: 22
Detection of Invasive Species (Siam Weed) Using Drone-Based Imaging and YOLO Deep Learning Model
Deepak Gautam, Zulfadli Mawardi, Louis Elliott, et al.
Remote Sensing (2025) Vol. 17, Iss. 1, pp. 120-120
Open Access | Times Cited: 2
An Efficient Approach for Crops Pests Recognition and Classification Based on Novel DeepPestNet Deep Learning Model
Naeem Ullah, Javed Ali Khan, Lubna A. Alharbi, et al.
IEEE Access (2022) Vol. 10, pp. 73019-73032
Open Access | Times Cited: 66
Deep learning for detecting herbicide weed control spectrum in turfgrass
Xiaojun Jin, Muthukumar Bagavathiannan, Aniruddha Maity, et al.
Plant Methods (2022) Vol. 18, Iss. 1
Open Access | Times Cited: 43
SE-YOLOv5x: An Optimized Model Based on Transfer Learning and Visual Attention Mechanism for Identifying and Localizing Weeds and Vegetables
Jianlin Zhang, Wen‐Hao Su, Heyi Zhang, et al.
Agronomy (2022) Vol. 12, Iss. 9, pp. 2061-2061
Open Access | Times Cited: 40
Weed Detection Using Deep Learning: A Systematic Literature Review
Nafeesa Yousuf Murad, Tariq Mahmood, Abdur Rahim Mohammad Forkan, et al.
Sensors (2023) Vol. 23, Iss. 7, pp. 3670-3670
Open Access | Times Cited: 37
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
A comprehensive survey on weed and crop classification using machine learning and deep learning
Faisal Dharma Adhinata, Wahyono Wahyono, Raden Sumiharto
Artificial Intelligence in Agriculture (2024) Vol. 13, pp. 45-63
Open Access | Times Cited: 16
Transfer and zero-shot learning for scalable weed detection and classification in UAV images
Nicolas Belissent, José M. Peña, Gustavo A. Mesías-Ruiz, et al.
Knowledge-Based Systems (2024) Vol. 292, pp. 111586-111586
Open Access | Times Cited: 15
Comparative performance of YOLOv8, YOLOv9, YOLOv10, YOLOv11 and Faster R-CNN models for detection of multiple weed species
Akhilesh Sharma, Vipan Kumar, Louis Longchamps
Smart Agricultural Technology (2024) Vol. 9, pp. 100648-100648
Open Access | Times Cited: 14
TSP-yolo-based deep learning method for monitoring cabbage seedling emergence
Xin Chen, Teng Liu, Kang Han, et al.
European Journal of Agronomy (2024) Vol. 157, pp. 127191-127191
Closed Access | Times Cited: 12
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
Integration of Remote Sensing and Machine Learning for Precision Agriculture: A Comprehensive Perspective on Applications
Jun Wang, Yanlong Wang, Guang Li, et al.
Agronomy (2024) Vol. 14, Iss. 9, pp. 1975-1975
Open Access | Times Cited: 12
Development of a Detection System for Types of Weeds in Maize (Zea mays L.) under Greenhouse Conditions Using the YOLOv5 v7.0 Model
Oscar Leonardo García-Navarrete, O. Santamaría, Pablo Martín‐Ramos, et al.
Agriculture (2024) Vol. 14, Iss. 2, pp. 286-286
Open Access | Times Cited: 10
Development and evaluation of a machine vision and deep learning-based smart sprayer system for site-specific weed management in row crops: An edge computing approach
Arjun Upadhyay, G C Sunil, Yu Zhang, et al.
Journal of Agriculture and Food Research (2024) Vol. 18, pp. 101331-101331
Open Access | Times Cited: 9
Weed Detection in Peanut Fields Based on Machine Vision
Hui Zhang, Zhi Wang, Yufeng Guo, et al.
Agriculture (2022) Vol. 12, Iss. 10, pp. 1541-1541
Open Access | Times Cited: 33
Weed detection to weed recognition: reviewing 50 years of research to identify constraints and opportunities for large-scale cropping systems
Guy Coleman, Asher Bender, Kun Hu, et al.
Weed Technology (2022) Vol. 36, Iss. 6, pp. 741-757
Open Access | Times Cited: 32
Formation of a Lightweight, Deep Learning-Based Weed Detection System for a Commercial Autonomous Laser Weeding Robot
Hafiza Sundus Fatima, Imtiaz Ul Hassan, Shehzad Hasan, et al.
Applied Sciences (2023) Vol. 13, Iss. 6, pp. 3997-3997
Open Access | Times Cited: 20
A smart sprayer for weed control in bermudagrass turf based on the herbicide weed control spectrum
Xiaojun Jin, Patrick E. McCullough, Teng Liu, et al.
Crop Protection (2023) Vol. 170, pp. 106270-106270
Closed Access | Times Cited: 17
Intraoperative AI‐assisted early prediction of parathyroid and ischemia alert in endoscopic thyroid surgery
Bo Wang, Jia‐Fan Yu, Si‐Ying Lin, et al.
Head & Neck (2024) Vol. 46, Iss. 8, pp. 1975-1987
Closed Access | Times Cited: 8
Detection and coverage estimation of purple nutsedge in turf with image classification neural networks
Xiaojun Jin, Kang Han, Hua Zhao, et al.
Pest Management Science (2024) Vol. 80, Iss. 7, pp. 3504-3515
Closed Access | Times Cited: 8
Evaluation of two deep learning‐based approaches for detecting weeds growing in cabbage
Hu Sun, Teng Liu, Jinxu Wang, et al.
Pest Management Science (2024) Vol. 80, Iss. 6, pp. 2817-2826
Closed Access | Times Cited: 7
Field-based multispecies weed and crop detection using ground robots and advanced YOLO models: A data and model-centric approach
G C Sunil, Arjun Upadhyay, Yu Zhang, et al.
Smart Agricultural Technology (2024) Vol. 9, pp. 100538-100538
Open Access | Times Cited: 7
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