Open Access Helper

OpenAlex Citation Counts

OpenAlex Citations Logo

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:

Damage detection of in-service steel railway bridges using a fine k-nearest neighbor machine learning classifier
Alireza Ghiasi, Ching‐Tai Ng, Abdul Hamid Sheikh
Structures (2022) Vol. 45, pp. 1920-1935
Closed Access | Times Cited: 28

Showing 1-25 of 28 citing articles:

Towards vibration-based damage detection of civil engineering structures: overview, challenges, and future prospects
Ali Zar, Zahoor Hussain, Muhammad Akbar, et al.
International Journal of Mechanics and Materials in Design (2024) Vol. 20, Iss. 3, pp. 591-662
Open Access | Times Cited: 15
Generalization of anomaly detection in bridge structures using a vibration‐based Siamese convolutional neural network
Alireza Ghiasi, Zhen Zhang, Zijie Zeng, et al.
Computer-Aided Civil and Infrastructure Engineering (2025)
Open Access | Times Cited: 2
The State of the Art of Artificial Intelligence Approaches and New Technologies in Structural Health Monitoring of Bridges
Raffaele Zinno, Sina Shaffiee Haghshenas, Giuseppe Guido, et al.
Applied Sciences (2022) Vol. 13, Iss. 1, pp. 97-97
Open Access | Times Cited: 53
Algorithms and Techniques for the Structural Health Monitoring of Bridges: Systematic Literature Review
Omar S. Sonbul, Muhammad Rashid
Sensors (2023) Vol. 23, Iss. 9, pp. 4230-4230
Open Access | Times Cited: 24
An unsupervised machine learning approach for real-time damage detection in bridges
Imane Bayane, John Leander, Raid Karoumi
Engineering Structures (2024) Vol. 308, pp. 117971-117971
Open Access | Times Cited: 10
Review on recent advances in structural health monitoring paradigm for looseness detection in bolted assemblies
Nikesh Chelimilla, Viswanath Chinthapenta, Naresh Kali, et al.
Structural Health Monitoring (2023) Vol. 22, Iss. 6, pp. 4264-4304
Closed Access | Times Cited: 21
Employing histogram of oriented gradient to enhance concrete crack detection performance with classification algorithm and Bayesian optimization
Zhen Sun, Elsa Caetano, Sérgio Pereira, et al.
Engineering Failure Analysis (2023) Vol. 150, pp. 107351-107351
Closed Access | Times Cited: 19
From data to insight, enhancing structural health monitoring using physics-informed machine learning and advanced data collection methods
Syed Haider Mehdi Rizvi, Muntazir Abbas
Engineering Research Express (2023) Vol. 5, Iss. 3, pp. 032003-032003
Open Access | Times Cited: 18
Bridge Damage Detection with Support Vector Machine in Accelerometer-Based Wireless Sensor Network
Willy Aulia Akbar Kustiana, Bambang Riyanto Trilaksono, Muhammad Riyansyah, et al.
Journal of Vibration Engineering & Technologies (2024)
Open Access | Times Cited: 5
Multidimensional dominant mapping eigenvalues fusion-driven method for structural damage identification and crack tip energy characterization
Lin Zhu, Junhao Wang, Min Chen, et al.
Structures (2025) Vol. 72, pp. 108266-108266
Closed Access
From traditional damage detection methods to Physics-Informed Machine Learning in bridges: A review
Safae Mammeri, Brais Barros, Borja Conde, et al.
Engineering Structures (2025) Vol. 330, pp. 119862-119862
Closed Access
GRNN-based cascade ensemble model for non-destructive damage state identification: small data approach
Ivan Izonin, Athanasia K. Kazantzi, Roman Tkachenko, et al.
Engineering With Computers (2024) Vol. 41, Iss. 1, pp. 723-738
Open Access | Times Cited: 3
Intelligent design of limit states for recycled aggregate concrete filled steel tubular columns
Keyu Chen, Shiqi Wang, Ying Wang, et al.
Structures (2023) Vol. 58, pp. 105338-105338
Closed Access | Times Cited: 10
A Supervised Machine Learning Monitoring System for Vehicle-Railway Bridge Collision
Khaled Hallak, Adel Abdallah
Artificial Intelligence and Applications (2024) Vol. 2, Iss. 4, pp. 343-357
Open Access | Times Cited: 3
Integrating electro-mechanical impedance data with machine learning for damage detection and classification of blended concrete systems
Gomasa Ramesh, Visalakshi Talakokula, Sri Kalyana Rama Jyosyula, et al.
Construction and Building Materials (2024) Vol. 445, pp. 137725-137725
Closed Access | Times Cited: 2
Leveraging Deep Learning for Robust Structural Damage Detection and Classification: A Transfer Learning Approach via CNN
Burak Duran, Saeed Eftekhar Azam, Masoud Sanayei
Infrastructures (2024) Vol. 9, Iss. 12, pp. 229-229
Open Access | Times Cited: 2
Neighborhood component analysis-based feature selection in machine learning to predict tendon ultimate stress of unbonded prestressed concrete beams
Zhaodong Ding, Hexiang Liu, Cristoforo Demartino, et al.
Case Studies in Construction Materials (2024) Vol. 21, pp. e03428-e03428
Open Access | Times Cited: 1
Combined two-level guided wave structural health monitoring strategy using multifeature integration and machine learning: application to early-age grouted sleeves
Jiahe Liu, Jun Yi, Dongsheng Li, et al.
Smart Materials and Structures (2023) Vol. 32, Iss. 9, pp. 095026-095026
Closed Access | Times Cited: 4
Seeking a Sufficient Data Volume for Railway Infrastructure Component Detection with Computer Vision Models
Alicja Gosiewska, Zuzanna Baran, Monika Baran, et al.
Sensors (2023) Vol. 23, Iss. 18, pp. 7776-7776
Open Access | Times Cited: 3
A Review on design and analysis of steel bridge with identification of load bearing capacity
Mohini Dharwe, Mohit Kumar Prajapati
International Journal of Advanced Engineering Research and Science (2023) Vol. 10, Iss. 1, pp. 122-127
Open Access | Times Cited: 2
Railroad Track Damage Detection Using CLAHE-KNN (CLAHE K-Nearest Neighbor)
Handrie Noprisson, Vina Ayumi
JSAI (Journal Scientific and Applied Informatics) (2023) Vol. 6, Iss. 2, pp. 274-279
Open Access | Times Cited: 2
Pengaruh Klasifikasi Sentimen Pada Ulasan Produk Amazon Berbasis Rekayasa Fitur dan <i>K-Nearest Negihbor</i>
Nitami Lestari Putri, Budi Warsito, Bayu Surarso
Jurnal Teknologi Informasi dan Ilmu Komputer (2024) Vol. 11, Iss. 1, pp. 65-74
Open Access
Estimation of nosing load in existing railway transom top bridges based on field testing and finite element modelling
Alireza Ghiasi, Daniel Lee
Advances in Bridge Engineering (2024) Vol. 5, Iss. 1
Open Access
Bridge assessment based on deflection as a measure of damage using Machine Learning-enhanced pattern identification
Francesco Pentassuglia, Athanasia K. Kazantzi, Asaad Faramarzi, et al.
Procedia Structural Integrity (2024) Vol. 64, pp. 254-261
Open Access
Audio feature augmentation for bolt looseness classification in data-deficient scenarios using machine learning
Nikesh Chelimilla, Viswanath Chinthapenta, Srikanth Korla
Nondestructive Testing And Evaluation (2024), pp. 1-24
Closed Access
Page 1 - Next Page

Scroll to top