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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:

Traffic Accident’s Severity Prediction: A Deep-Learning Approach-Based CNN Network
Ming Zheng, Tong Li, Rui Zhu, et al.
IEEE Access (2019) Vol. 7, pp. 39897-39910
Open Access | Times Cited: 140

Showing 1-25 of 140 citing articles:

Conditional Wasserstein generative adversarial network-gradient penalty-based approach to alleviating imbalanced data classification
Ming Zheng, Tong Li, Rui Zhu, et al.
Information Sciences (2019) Vol. 512, pp. 1009-1023
Closed Access | Times Cited: 155
A deep learning based traffic crash severity prediction framework
Md Adilur Rahim, Hany M. Hassan
Accident Analysis & Prevention (2021) Vol. 154, pp. 106090-106090
Closed Access | Times Cited: 124
Injury severity prediction of traffic crashes with ensemble machine learning techniques: a comparative study
Arshad Jamal, Muhammad Zahid, Muhammad Tauhidur Rahman, et al.
International Journal of Injury Control and Safety Promotion (2021) Vol. 28, Iss. 4, pp. 408-427
Closed Access | Times Cited: 108
Prioritizing rear-end crash explanatory factors for injury severity level using deep learning and global sensitivity analysis
Mahmoud Owais, Abdullah Mohammed Alshehri, Jayadev Gyani, et al.
Expert Systems with Applications (2024) Vol. 245, pp. 123114-123114
Closed Access | Times Cited: 24
Learning spatial patterns and temporal dependencies for traffic accident severity prediction: A deep learning approach
Fares Alhaek, Weichao Liang, Taha M. Rajeh, et al.
Knowledge-Based Systems (2024) Vol. 286, pp. 111406-111406
Closed Access | Times Cited: 24
Modern data sources and techniques for analysis and forecast of road accidents: A review
Camilo Gutierrez-Osorio, César Pedraza
Journal of Traffic and Transportation Engineering (English Edition) (2020) Vol. 7, Iss. 4, pp. 432-446
Open Access | Times Cited: 120
Handling Imbalanced Data in Road Crash Severity Prediction by Machine Learning Algorithms
Nicholas Fiorentini, Massimo Losa
Infrastructures (2020) Vol. 5, Iss. 7, pp. 61-61
Open Access | Times Cited: 105
An Automatic Car Accident Detection Method Based on Cooperative Vehicle Infrastructure Systems
Daxin Tian, Chuang Zhang, Xuting Duan, et al.
IEEE Access (2019) Vol. 7, pp. 127453-127463
Open Access | Times Cited: 98
Review on big data applications in safety research of intelligent transportation systems and connected/automated vehicles
Yanqi Lian, Guoqing Zhang, Jaeyoung Lee, et al.
Accident Analysis & Prevention (2020) Vol. 146, pp. 105711-105711
Closed Access | Times Cited: 81
Applications of machine learning methods in traffic crash severity modelling: current status and future directions
Xiao Wen, Yuanchang Xie, Liming Jiang, et al.
Transport Reviews (2021) Vol. 41, Iss. 6, pp. 855-879
Closed Access | Times Cited: 60
Traffic Accident Severity Prediction Based on Random Forest
Miaomiao Yan, Yindong Shen
Sustainability (2022) Vol. 14, Iss. 3, pp. 1729-1729
Open Access | Times Cited: 59
Investigating the influence of streetscape environmental characteristics on pedestrian crashes at intersections using street view images and explainable machine learning
Han Yue
Accident Analysis & Prevention (2024) Vol. 205, pp. 107693-107693
Closed Access | Times Cited: 11
Advancing urban traffic accident forecasting through sparse spatio-temporal dynamic learning
Pengfei Cui, Xiaobao Yang, Mohamed Abdel‐Aty, et al.
Accident Analysis & Prevention (2024) Vol. 200, pp. 107564-107564
Closed Access | Times Cited: 10
Predicting Crash Injury Severity with Machine Learning Algorithm Synergized with Clustering Technique: A Promising Protocol
Khaled Assi, Syed Masiur Rahman, Umer Mansoor, et al.
International Journal of Environmental Research and Public Health (2020) Vol. 17, Iss. 15, pp. 5497-5497
Open Access | Times Cited: 58
Deep learning support for intelligent transportation systems
Juan Antonio Guerrero Ibáñez, Juan Contreras‐Castillo, Sherali Zeadally
Transactions on Emerging Telecommunications Technologies (2020) Vol. 32, Iss. 3
Closed Access | Times Cited: 58
A review on neural network techniques for the prediction of road traffic accident severity
Md. Ebrahim Shaik, Md. Milon Islam, Quazi Sazzad Hossain
Asian Transport Studies (2021) Vol. 7, pp. 100040-100040
Open Access | Times Cited: 53
Freeway accident detection and classification based on the multi-vehicle trajectory data and deep learning model
Da Yang, Yuezhu Wu, Feng Sun, et al.
Transportation Research Part C Emerging Technologies (2021) Vol. 130, pp. 103303-103303
Closed Access | Times Cited: 51
Extraction of decision rules using genetic algorithms and simulated annealing for prediction of severity of traffic accidents by motorcyclists
Holman Ospina-Mateus, Leonardo Quintana, Francisco J. López‐Valdés, et al.
Journal of Ambient Intelligence and Humanized Computing (2021) Vol. 12, Iss. 11, pp. 10051-10072
Closed Access | Times Cited: 40
UFFDFR: Undersampling framework with denoising, fuzzy c-means clustering, and representative sample selection for imbalanced data classification
Ming Zheng, Tong Li, Xiaoyao Zheng, et al.
Information Sciences (2021) Vol. 576, pp. 658-680
Closed Access | Times Cited: 40
Classification of truck-involved crash severity: Dealing with missing, imbalanced, and high dimensional safety data
Seyed Iman Mohammadpour, Majid Khedmati, Mohammad Javad Hassan Zada
PLoS ONE (2023) Vol. 18, Iss. 3, pp. e0281901-e0281901
Open Access | Times Cited: 16
Traffic Flow Prediction Based on Spatio-Temporal Dependent Graph Neural Network
淼玉 周
Advances in Applied Mathematics (2025) Vol. 14, Iss. 03, pp. 314-325
Closed Access
Variance-based global sensitivity analysis for rear-end crash investigation using deep learning
Ghada Moussa, Mahmoud Owais, Essam Dabbour
Accident Analysis & Prevention (2021) Vol. 165, pp. 106514-106514
Closed Access | Times Cited: 34
Deep Learning Ensemble Model for the Prediction of Traffic Accidents Using Social Media Data
Camilo Gutierrez-Osorio, Fabio A. González, César Pedraza
Computers (2022) Vol. 11, Iss. 9, pp. 126-126
Open Access | Times Cited: 25
Predicting Traffic Casualties Using Support Vector Machines with Heuristic Algorithms: A Study Based on Collision Data of Urban Roads
Weifan Zhong, Lijing Du
Sustainability (2023) Vol. 15, Iss. 4, pp. 2944-2944
Open Access | Times Cited: 14
GIS-Based Spatial Analysis Model for Assessing Impact and Cumulative Risk in Road Traffic Accidents via Analytic Hierarchy Process (AHP)—Case Study: Romania
Ștefan Bilașco, Titus Man
Applied Sciences (2024) Vol. 14, Iss. 6, pp. 2643-2643
Open Access | Times Cited: 4
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