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Mohammad R. Jahanshahi
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Year
NB-CNN: Deep learning-based crack detection using convolutional neural network and Na´ve Bayes data fusion
FC Chen, MR Jahanshahi
IEEE Transactions on Industrial Electronics 65 (5), 4392-4400, 2018
9112018
Evaluation of deep learning approaches based on convolutional neural networks for corrosion detection
DJ Atha, MR Jahanshahi
Structural Health Monitoring 17 (5), 1110-1128, 2018
3202018
An innovative methodology for detection and quantification of cracks through incorporation of depth perception
MR Jahanshahi, SF Masri, CW Padgett, GS Sukhatme
Machine vision and applications 24 (2), 227-241, 2013
2932013
Automated defect classification in sewer closed circuit television inspections using deep convolutional neural networks
SS Kumar, DM Abraham, MR Jahanshahi, T Iseley, J Starr
Automation in Construction 91, 273-283, 2018
2302018
A survey and evaluation of promising approaches for automatic image-based defect detection of bridge structures
MR Jahanshahi, JS Kelly, SF Masri, GS Sukhatme
Structure and Infrastructure Engineering 5 (6), 455-486, 2009
1952009
Data fusion approaches for structural health monitoring and system identification: Past, present, and future
RT Wu, MR Jahanshahi
Structural Health Monitoring 19 (2), 552-586, 2020
1732020
Deep convolutional neural network for structural dynamic response estimation and system identification
RT Wu, MR Jahanshahi
Journal of Engineering Mechanics 145 (1), 04018125, 2019
1732019
Unsupervised approach for autonomous pavement-defect detection and quantification using an inexpensive depth sensor
MR Jahanshahi, F Jazizadeh, SF Masri, B Becerik-Gerber
Journal of Computing in Civil Engineering 27 (6), 743-754, 2013
1672013
A texture‐based video processing methodology using Bayesian data fusion for autonomous crack detection on metallic surfaces
FC Chen, MR Jahanshahi, RT Wu, C Joffe
Computer‐Aided Civil and Infrastructure Engineering 32 (4), 271-287, 2017
1562017
A new methodology for non-contact accurate crack width measurement through photogrammetry for automated structural safety evaluation
MR Jahanshahi, SF Masri
Smart materials and structures 22 (3), 035019, 2013
1332013
Deep learning–based automated detection of sewer defects in CCTV videos
SS Kumar, M Wang, DM Abraham, MR Jahanshahi, T Iseley, JCP Cheng
Journal of Computing in Civil Engineering 34 (1), 04019047, 2020
1192020
Deep learning‐based multi‐class damage detection for autonomous post‐disaster reconnaissance
T Ghosh Mondal, MR Jahanshahi, RT Wu, ZY Wu
Structural Control and Health Monitoring 27 (4), e2507, 2020
1032020
Pruning deep convolutional neural networks for efficient edge computing in condition assessment of infrastructures
RT Wu, A Singla, MR Jahanshahi, E Bertino, BJ Ko, D Verma
Computer‐Aided Civil and Infrastructure Engineering 34 (9), 774-789, 2019
952019
Autonomous pavement condition assessment
MR Jahanshahi, FJ Karimi, SF Masri, B Becerik-Gerber
US Patent 9,196,048, 2015
922015
Multi-image stitching and scene reconstruction for evaluating defect evolution in structures
MR Jahanshahi, SF Masri, GS Sukhatme
Structural Health Monitoring 10 (6), 643-657, 2011
922011
Inexpensive multimodal sensor fusion system for autonomous data acquisition of road surface conditions
YL Chen, MR Jahanshahi, P Manjunatha, WP Gan, M Abdelbarr, SF Masri, ...
IEEE Sensors Journal 16 (21), 7731-7743, 2016
672016
Image-based crack quantification
MR Jahanshahi, S Masri
US Patent 9,235,902, 2016
572016
3D dynamic displacement-field measurement for structural health monitoring using inexpensive RGB-D based sensor
M Abdelbarr, YL Chen, MR Jahanshahi, SF Masri, WM Shen, UA Qidwai
Smart materials and structures 26 (12), 125016, 2017
532017
An evaluation of image‐based structural health monitoring using integrated unmanned aerial vehicle platform
MA Akbar, U Qidwai, MR Jahanshahi
Structural Control and Health Monitoring 26 (1), e2276, 2019
522019
Parametric performance evaluation of wavelet-based corrosion detection algorithms for condition assessment of civil infrastructure systems
MR Jahanshahi, SF Masri
Journal of Computing in Civil Engineering 27 (4), 345-357, 2013
492013
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