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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:

Image Based Techniques for Crack Detection, Classification and Quantification in Asphalt Pavement: A Review
Hamzeh Zakeri, Fereidoon Moghadas Nejad, Ahmad Fahimifar
Archives of Computational Methods in Engineering (2016) Vol. 24, Iss. 4, pp. 935-977
Closed Access | Times Cited: 239

Showing 26-50 of 239 citing articles:

Survey on performance of deep learning models for detecting road damages using multiple dashcam image resources
Minh-Tu Cao, Quoc‐Viet Tran, Ngoc‐Mai Nguyen, et al.
Advanced Engineering Informatics (2020) Vol. 46, pp. 101182-101182
Closed Access | Times Cited: 105
Automated Visual Defect Classification for Flat Steel Surface: A Survey
Qiwu Luo, Xiaoxin Fang, Jiaojiao Su, et al.
IEEE Transactions on Instrumentation and Measurement (2020) Vol. 69, Iss. 12, pp. 9329-9349
Open Access | Times Cited: 90
RCNet: road classification convolutional neural networks for intelligent vehicle system
Deepak Kumar Dewangan, Satya Prakash Sahu
Intelligent Service Robotics (2021) Vol. 14, Iss. 2, pp. 199-214
Closed Access | Times Cited: 88
Research and applications of artificial neural network in pavement engineering: A state-of-the-art review
Xu Yang, Jinchao Guan, Ling Ding, et al.
Journal of Traffic and Transportation Engineering (English Edition) (2021) Vol. 8, Iss. 6, pp. 1000-1021
Open Access | Times Cited: 86
Two-stage convolutional neural network for road crack detection and segmentation
Nhung Hong Thi Nguyen, Stuart Perry, Donald J. Bone, et al.
Expert Systems with Applications (2021) Vol. 186, pp. 115718-115718
Open Access | Times Cited: 85
Crack Detection from a Concrete Surface Image Based on Semantic Segmentation Using Deep Learning
Tatsuro Yamane, Pang-jo CHUN
Journal of Advanced Concrete Technology (2020) Vol. 18, Iss. 9, pp. 493-504
Open Access | Times Cited: 84
Automatic detection of asphalt pavement raveling using image texture based feature extraction and stochastic gradient descent logistic regression
Nhat‐Duc Hoang
Automation in Construction (2019) Vol. 105, pp. 102843-102843
Closed Access | Times Cited: 81
Convolutional neural networks for 5G-enabled Intelligent Transportation System : A systematic review
Deepika Sirohi, Neeraj Kumar, Prashant Singh Rana
Computer Communications (2020) Vol. 153, pp. 459-498
Closed Access | Times Cited: 74
Machine learning algorithms for monitoring pavement performance
Saúl Cano-Ortiz, Pablo Pascual-Muñoz, Daniel Castro‐Fresno
Automation in Construction (2022) Vol. 139, pp. 104309-104309
Open Access | Times Cited: 64
RUC-Net: A Residual-Unet-Based Convolutional Neural Network for Pixel-Level Pavement Crack Segmentation
Gui Yu, Juming Dong, Yihang Wang, et al.
Sensors (2022) Vol. 23, Iss. 1, pp. 53-53
Open Access | Times Cited: 52
Data Augmentation and Intelligent Recognition in Pavement Texture Using a Deep Learning
Ning Chen, Zijin Xu, Zhuo Liu, et al.
IEEE Transactions on Intelligent Transportation Systems (2022) Vol. 23, Iss. 12, pp. 25427-25436
Closed Access | Times Cited: 38
Image Processing Techniques for Concrete Crack Detection: A Scientometrics Literature Review
Md. Al-Masrur Khan, Seong‐Hoon Kee, Al‐Sakib Khan Pathan, et al.
Remote Sensing (2023) Vol. 15, Iss. 9, pp. 2400-2400
Open Access | Times Cited: 28
Review of advanced road materials, structures, equipment, and detection technologies
Maria Chiara Cavalli, Chen De, Qian Chen, et al.
Journal of Road Engineering (2023) Vol. 3, Iss. 4, pp. 370-468
Open Access | Times Cited: 28
Prospect of 3D printing technologies in maintenance of asphalt pavement cracks and potholes
Fangyuan Gong, Xuejiao Cheng, Bingjie Fang, et al.
Journal of Cleaner Production (2023) Vol. 397, pp. 136551-136551
Closed Access | Times Cited: 25
Crack assessment using multi-sensor fusion simultaneous localization and mapping (SLAM) and image super-resolution for bridge inspection
Chu-Qiao Feng, Bao‐Luo Li, Yu-Fei Liu, et al.
Automation in Construction (2023) Vol. 155, pp. 105047-105047
Closed Access | Times Cited: 22
Multi-stage generative adversarial networks for generating pavement crack images
Chengjia Han, Tao Ma, Ju Huyan, et al.
Engineering Applications of Artificial Intelligence (2024) Vol. 131, pp. 107767-107767
Closed Access | Times Cited: 13
Automatic crack detection on concrete and asphalt surfaces using semantic segmentation network with hierarchical Transformer
Hubing Li, Haowei Zhang, Hong Zhu, et al.
Engineering Structures (2024) Vol. 307, pp. 117903-117903
Closed Access | Times Cited: 12
Road Surface Defect Detection—From Image-Based to Non-Image-Based: A Survey
Jongmin Yu, Jiaqi Jiang, Sebastiano Fichera, et al.
IEEE Transactions on Intelligent Transportation Systems (2024) Vol. 25, Iss. 9, pp. 10581-10603
Open Access | Times Cited: 7
Image processing based automatic recognition of asphalt pavement patch using a metaheuristic optimized machine learning approach
Nhat‐Duc Hoang
Advanced Engineering Informatics (2019) Vol. 40, pp. 110-120
Closed Access | Times Cited: 67
Segment-based pavement crack quantification
Xingxing Weng, Yuchun Huang, Wenzong Wang
Automation in Construction (2019) Vol. 105, pp. 102819-102819
Closed Access | Times Cited: 63
Automatic crack recognition for concrete bridges using a fully convolutional neural network and naive Bayes data fusion based on a visual detection system
Gang Li, Qiangwei Liu, Shanmeng Zhao, et al.
Measurement Science and Technology (2020) Vol. 31, Iss. 7, pp. 075403-075403
Closed Access | Times Cited: 62
Pavement Crack Detection based on yolo v3
Mingxin Nie, Cheng Wang
2019 2nd International Conference on Safety Produce Informatization (IICSPI) (2019), pp. 327-330
Closed Access | Times Cited: 55
Intelligent Road Inspection with Advanced Machine Learning; Hybrid Prediction Models for Smart Mobility and Transportation Maintenance Systems
Nader Karballaeezadeh, Farah Zaremotekhases, Shahaboddin Shamshirband, et al.
Energies (2020) Vol. 13, Iss. 7, pp. 1718-1718
Open Access | Times Cited: 52
A review of deep learning methods for pixel-level crack detection
Hongxia Li, Weixing Wang, Mengfei Wang, et al.
Journal of Traffic and Transportation Engineering (English Edition) (2022) Vol. 9, Iss. 6, pp. 945-968
Open Access | Times Cited: 35
A Novel Approach for Detection of Pavement Crack and Sealed Crack Using Image Processing and Salp Swarm Algorithm Optimized Machine Learning
Nhat‐Duc Hoang, Thanh‐Canh Huynh, Xuan-Linh Tran, et al.
Advances in Civil Engineering (2022) Vol. 2022, Iss. 1
Open Access | Times Cited: 32

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