Deep learning-based crack damage detection using convolutional neural networks YJ Cha, W Choi, O Buyukozturk Computer-Aided Civil and Infrastructure Engineering 32 (5), 361-378, 2016 | 2965 | 2016 |
Autonomous structural visual inspection using region‐based deep learning for detecting multiple damage types YJ Cha, W Choi, G Suh, S Mahmoudkhani, O Büyüköztürk Computer‐Aided Civil and Infrastructure Engineering, 2017 | 1331 | 2017 |
Modal identification of simple structures with high-speed video using motion magnification JG Chen, N Wadhwa, YJ Cha, F Durand, WT Freeman, O Buyukozturk Journal of Sound and Vibration 345, 58-71, 2015 | 524 | 2015 |
Autonomous UAVs for structural health monitoring using deep learning and an ultrasonic beacon system with geo‐tagging D Kang, YJ Cha Computer‐Aided Civil and Infrastructure Engineering, 2018 | 332 | 2018 |
SDDNet: Real-time crack segmentation W Choi, YJ Cha IEEE Transactions on Industrial Electronics, 2019 | 304 | 2019 |
Vision-based detection of loosened bolts using the Hough transform and support vector machines YJ Cha, K You, W Choi Automation in Construction 71, 181-188, 2016 | 286 | 2016 |
Hybrid pixel-level concrete crack segmentation and quantification across complex backgrounds using deep learning D Kang, SS Benipal, DL Gopal, YJ Cha Automation in Construction 118, 103291, 2020 | 266 | 2020 |
Structural damage detection using modal strain energy and hybrid multiobjective optimization YJ Cha, O Buyukozturk Computer‐Aided Civil and Infrastructure Engineering 30 (5), 347-358, 2015 | 251 | 2015 |
Unsupervised deep learning approach using a deep auto-encoder with a one-class support vector machine to detect damage Z Wang, YJ Cha Structural Health Monitoring 20 (1), 406-425, 2021 | 209 | 2021 |
Deep learning-based automatic volumetric damage quantification using depth camera GH Beckman, D Polyzois, YJ Cha Automation in Construction 99, 114-124, 2019 | 194 | 2019 |
Output-only computer vision based damage detection using phase-based optical flow and unscented Kalman filters YJ Cha, JG Chen, O Büyüköztürk Engineering Structures 132, 300-313, 2017 | 181 | 2017 |
Efficient attention-based deep encoder and decoder for automatic crack segmentation DH Kang, YJ Cha Structural Health Monitoring 21 (5), 2190-2205, 2022 | 158 | 2022 |
Fully automated vision-based loosened bolt detection using the Viola–Jones algorithm L Ramana, W Choi, YJ Cha Structural Health Monitoring 18 (2), 422-434, 2019 | 127 | 2019 |
Unsupervised novelty detection–based structural damage localization using a density peaks-based fast clustering algorithm YJ Cha, Z Wang Structural Health Monitoring 17 (2), 313-324, 2018 | 123 | 2018 |
Subsurface damage detection of a steel bridge using deep learning and uncooled micro-bolometer R Ali, YJ Cha Construction and Building Materials 226, 376-387, 2019 | 122 | 2019 |
Attention-based generative adversarial network with internal damage segmentation using thermography R Ali, YJ Cha Automation in Construction 141, 104412, 2022 | 118 | 2022 |
Real-time multiple damage mapping using autonomous UAV and deep faster region-based neural networks for GPS-denied structures R Ali, D Kang, G Suh, YJ Cha Automation in Construction 130, 103831, 2021 | 99 | 2021 |
Multi-objective genetic algorithms for cost-effective distributions of actuators and sensors in large structures YJ Cha, AK Agrawal, Y Kim, AM Raich Expert Systems with Applications 39 (9), 7822-7833, 2012 | 98 | 2012 |
Structural modal identification through high speed camera video: Motion magnification JG Chen, N Wadhwa, YJ Cha, F Durand, WT Freeman, O Buyukozturk Topics in Modal Analysis I, Volume 7: Proceedings of the 32nd IMAC, A …, 2014 | 89 | 2014 |
Large-scale real-time hybrid simulation for evaluation of advanced damping system performance A Friedman, SJ Dyke, B Phillips, R Ahn, B Dong, Y Chae, N Castaneda, ... Journal of Structural Engineering 141 (6), 04014150, 2015 | 87 | 2015 |