OOIR: Observatory of International Research

Papers

(The H4-Index of Computer-Aided Civil and Infrastructure Engineering is 38. The table below lists those papers that are above that threshold based on CrossRef citation counts [max. 250 papers]. The publications cover those that have been published in the past four years, i.e., from 2020-11-01 to 2024-11-01.)

Article	Citations
Graph neural network and reinforcement learning for multi‐agent cooperative control of connected autonomous vehicles	130
Efficient training of physics‐informed neural networks via importance sampling	122
Automatic detection method of tunnel lining multi‐defects via an enhanced You Only Look Once network	120
Optimization of electric bus scheduling considering stochastic volatilities in trip travel time and energy consumption	109
Crack detection using fusion features‐based broad learning system and image processing	90
Cross‐scene pavement distress detection by a novel transfer learning framework	87
Hybrid deep learning architecture for rail surface segmentation and surface defect detection	83
Early damage detection by an innovative unsupervised learning method based on kernel null space and peak‐over‐threshold	72
Deep learning for post‐hurricane aerial damage assessment of buildings	71
A deep learning‐based image captioning method to automatically generate comprehensive explanations of bridge damage	69
Tiny‐Crack‐Net: A multiscale feature fusion network with attention mechanisms for segmentation of tiny cracks	68
Homography‐based structural displacement measurement for large structures using unmanned aerial vehicles	66
Balanced semisupervised generative adversarial network for damage assessment from low‐data imbalanced‐class regime	61
Hybrid semantic segmentation for tunnel lining cracks based on Swin Transformer and convolutional neural network	61
Structural damage detection and localization using decision tree ensemble and vibration data	59
Dual attention deep learning network for automatic steel surface defect segmentation	58
Mechanical–transport–chemical modeling of electrochemical repair methods for corrosion‐induced cracking in marine concrete	55
Dynamics‐based cross‐domain structural damage detection through deep transfer learning	54
Multistage semisupervised active learning framework for crack identification, segmentation, and measurement of bridges	53
Autonomous detection of damage to multiple steel surfaces from 360° panoramas using deep neural networks	51
Bayesian‐optimized unsupervised learning approach for structural damage detection	51
Automated crack assessment and quantitative growth monitoring	50
A multi‐objective genetic algorithm strategy for robust optimal sensor placement	50
A novel U‐shaped encoder–decoder network with attention mechanism for detection and evaluation of road cracks at pixel level	49
A deep reinforcement learning approach to mountain railway alignment optimization	49

A knowledge‐enhanced deep reinforcement learning‐based shape optimizer for aerodynamic mitigation of wind‐sensitive structures	48
Deep semantic segmentation for visual understanding on construction sites	48
Multicategory damage detection and safety assessment of post‐earthquake reinforced concrete structures using deep learning	48
Real‐time structural displacement estimation by fusing asynchronous acceleration and computer vision measurements	48
Intelligent pixel‐level detection of multiple distresses and surface design features on asphalt pavements	47
Autoencoders for unsupervised real‐time bridge health assessment	45
Spatiotemporal gated graph attention network for urban traffic flow prediction based on license plate recognition data	44
A platoon regulation algorithm to improve the traffic performance of highway work zones	43
A decentralized unsupervised structural condition diagnosis approach using deep auto‐encoders	43
A robust prediction model for displacement of concrete dams subjected to irregular water‐level fluctuations	41
Toward a general unsupervised novelty detection framework in structural health monitoring	40
Deep generative Bayesian optimization for sensor placement in structural health monitoring	39
Large‐scale structural health monitoring using composite recurrent neural networks and grid environments	39
A hierarchical framework for improving ride comfort of autonomous vehicles via deep reinforcement learning with external knowledge	38
A deep neural network framework for real‐time on‐site estimation of acceleration response spectra of seismic ground motions	38
Deep learning‐based object identification with instance segmentation and pseudo‐LiDAR point cloud for work zone safety	38