| Encoder–decoder network for pixel‐level road crack detection in black‐box images S Bang, S Park, H Kim, H Kim Computer‐Aided Civil and Infrastructure Engineering 34 (8), 713-727, 2019 | 392 | 2019 |
| Patch-based crack detection in black box images using convolutional neural networks S Park, S Bang, H Kim, H Kim Journal of Computing in Civil Engineering 33 (3), 04019017, 2019 | 131 | 2019 |
| Image retrieval using BIM and features from pretrained VGG network for indoor localization I Ha, H Kim, S Park, H Kim Building and Environment 140, 23-31, 2018 | 130 | 2018 |
| Image augmentation to improve construction resource detection using generative adversarial networks, cut-and-paste, and image transformation techniques S Bang, F Baek, S Park, W Kim, H Kim Automation in Construction 115, 103198, 2020 | 79 | 2020 |
| Vision-based nonintrusive context documentation for earthmoving productivity simulation H Kim, Y Ham, W Kim, S Park, H Kim Automation in Construction 102, 135-147, 2019 | 58 | 2019 |
| Synthetic data generation using building information models Y Hong, S Park, H Kim, H Kim Automation in Construction 130, 103871, 2021 | 35 | 2021 |
| A deep residual network with transfer learning for pixel-level road crack detection S Bang, S Park, H Kim, H Kim ISARC. Proceedings of the International Symposium on Automation and Robotics …, 2018 | 34 | 2018 |
| Computer vision–based estimation of flood depth in flooded-vehicle images S Park, F Baek, J Sohn, H Kim Journal of Computing in Civil Engineering 35 (2), 04020072, 2021 | 32 | 2021 |
| A comprehensive evaluation of factors influencing acceptance of robotic assistants in field construction work S Park, H Yu, CC Menassa, VR Kamat Journal of Management in Engineering 39 (3), 04023010, 2023 | 20 | 2023 |
| Conditional generative adversarial networks with adversarial attack and defense for generative data augmentation F Baek, D Kim, S Park, H Kim, SH Lee Journal of Computing in Civil Engineering 36 (3), 04022001, 2022 | 12 | 2022 |
| Data augmentation using adversarial training for construction-equipment classification F Baek, S Park, H Kim arXiv preprint arXiv:1911.11916, 2019 | 12 | 2019 |
| Patch-based crack detection in black box road images using deep learning S Park, S Bang, H Kim, H Kim ISARC. Proceedings of the International Symposium on Automation and Robotics …, 2018 | 10 | 2018 |
| Synthetic data generation for indoor scene understanding using BIM Y Hong, S Park, H Kim ISARC. Proceedings of the International Symposium on Automation and Robotics …, 2020 | 9 | 2020 |
| An image augmentation method for detecting construction resources using convolutional neural network and UAV images S Bang, F Baek, S Park, W Kim, H Kim Proceedings of the 36th International Symposium on Automation and Robotics …, 2019 | 6 | 2019 |
| Image-based indoor localization using BIM and features of CNN I Ha, H Kim, S Park, H Kim ISARC. Proceedings of the International Symposium on Automation and Robotics …, 2018 | 6 | 2018 |
| Natural language instructions for intuitive human interaction with robotic assistants in field construction work S Park, X Wang, CC Menassa, VR Kamat, J Chai Automation in Construction 161, 105345, 2024 | 2 | 2024 |
| Joint BERT Model for Intent Classification and Slot Filling Analysis of Natural Language Instructions in Co-Robotic Field Construction Work S Park, CC Menassa, VR Kamat Computing in Civil Engineering 2023, 453-460, 2024 | 1 | 2024 |
| Deep learning-based vehicle image matching for flooding damage estimation S Park, F Baek, J Sohn, H Kim Creative Construction Conference 2019, 38-41, 2019 | 1 | 2019 |
| Integrating Large Language Models with Multimodal Virtual Reality Interfaces to Support Collaborative Human-Robot Construction Work S Park, CC Menassa, VR Kamat arXiv preprint arXiv:2404.03498, 2024 | | 2024 |
| Real-time Knowledge Structure Mapping from Twitter for Damage Information Retrieval during a Disaster J Sohn, Y Kim, S Park, H Kim International conference on construction engineering and project management …, 2020 | | 2020 |
Hyoungkwan KimYonsei University在 yonsei.ac.kr 的电子邮件经过验证
