JKSCE
KSCE JOURNAL OF CIVIL AND
ENVIRONMENTAL ENGINEERING RESEARCH
KSCE
Contact
ISSN : 1015-6348 (Print)
ISSN : 2799-9629 (Online)
Mobile QR Code
Journal of the Korean Society of Civil Engineers
ISO Journal Title
KSCE J. Civ. Environ. Eng. Res.
Open Access, Bi-monthly
Main Menu
Main Menu
최근호
Current Issue
논문집
Journal Archive
저널소개
About Journal
편집위원회
Editorial Board
논문투고안내
For Authors and Reviewers
윤리규정
Publication Ethics
Principles of Transparency and Best Practice
Business Model
연락처
Contact Info
논문투고
E-submission
Journal Search
Home
All Issues
2023-08
(v.43 n.4)
10.12652/Ksce.2023.43.4.0511
Journal XML
XML
PDF
INFO
REF
References
1
"Abdeljaber, O., Avci, O., Kiranyaz, S., Gabbouj, M. and Inman, D. J. (2017). “Real-time vibration-based structural damage detection using one-dimensional convolutional neural networks.” Journal of Sound and Vibration, Elsevier, Vol. 388, pp. 154-170, https://doi.org/10.1016/j.jsv.2016.10.043."
2
"Cha, Y. J., Choi, W. and Büyüköztürk, O. (2017). “Deep learning-based crack damage detection using convolutional neural network.” Computer-Aided Civil and Infrastructure Engineering, Wiley, Vol. 32, No. 5, pp. 361-378, https://doi.org/10.1111/mice.12263."
3
"Gao, Y. and Mosalam, K. M. (2018). “Deep transfer learning for image-based structural damage recognition.” Computer-Aided Civil and Infrastructure Engineering, Vol. 33, No. 9, pp. 748-768."
4
"Howard, A., Sandler, M., Chu, G., Chen, L.-C., Chen, B., Tan, M., Wang, W., Zhu, Y., Pang, R., Vasudevan, V., Le, Q. V. and Adam, H. (2019). “Searching for MobileNetV3.” arXiv preprint, https://arxiv.org/abs/1905.02244v5."
5
"Howard, A. G., Zhu, M., Chen, B., Kalenichenko, D., Wang, W., Weyand, T., Andreetto, M. and Adam, H. (2017). “MobileNets : efficient convolutional neural networks for mobile vision applications.” arXiv preprint, https://arxiv.org/abs/1704.04861v1."
6
"Kingma, D. P. and Ba, J. (2014). “ADAM: A method for stochastic optimization.” Proceedings of 3rd International Conference for Learning Representations, San Diego, USA, 2015, arXiv preprint, https://arxiv.org/abs/1412.6980."
7
"Krizhevsky, A., Sutskever, I. and Hinton, G. E. (2012). “Imagenet classification with deep convolutional neural networks.” Advances in Neural Information Processing Systems, MIT Press, Vol. 5, pp. 1097-1105."
8
"Kurbiel, T. and Khaleghian, S. (2017). “Training of deep neural networks based on distance measures using RMSProp.” arXiv preprint, https://arxiv.org/abs/1708.01911."
9
"Lin, Y., Nie, Z. and Ma, H. (2017). “Structural damage detection with automatic feature-extraction through deep learning.” Computer-Aided Civil and Infrastructure Engineering, Wiley, Vol. 32, No. 12, pp. 1025-1046, https://doi.org/10.1111/mice.12313."
10
"Nam, W. S., Jung, H., Park, K. H., Kim, C. M. and Kim, G. S. (2022). “Development of deep learning-based damage detection prototype for concrete bridge condition evaluation.” KSCE Journal of Civil and Environmental Engineering Research, KSCE, Vol. 42, No. 1, pp. 107-116, https://doi.org/10.12652/Ksce.2022.42.1.0107 (in Korean)."
11
"Sandler, M., Howard, A., Zhu, M., Zhmoginov, A. and Chen, L.-C. (2018). “Mobilenetv2 : Inverted residuals and linear bottlenecks.” https://arxiv.org/abs/1801.04381."
12
"Scherer, D., Műller, A. and Behnke, S. (2010). “Evaluation of pooling operations in convolutional architectures for object recognition.” Proceedings of 20th International Conference on Artificial Neural Networks (ICANN), Thessaloniki, Greece, pp. 92-101."
13
"Sifre, L. (2014). Rigid-motion scattering for image classification. PhD thesis, Ecole Polytechnique, CMAP, New York."
14
"Soukup, D. and Huber-Mork, R. (2014). “Convolutional neural networks for steel surface defect detection from photometric stereo images.” Proceedings of 10th International Symposium on Visual Computing, Las Vegas, NV, pp. 668-677."
15
"Srivastava, N., Hinton, G., Krizhevsky, A., Sutskever, I. and Salakhutdinov, R. (2014). “Dropout : A simple way to prevent neural networks from overfitting.” Journal of Machine Learning Research, JMLR.org, Vol. 15, No. 1, pp. 1929-1958."
16
"Vetrivel, A., Gerke, M., Kerl, N., Nex, F. and Vosselman, G. (2017). “Disaster damage detection through synergistic use of deep learning and 3D point cloud features derived from very high resolution oblique aerial images and multiple-kernel-learning.” ISPRS Journal of Photogrammetry and Remote Sensing, Elsevier, Vol. 140, pp. 45-59, https://doi.org/10.1016/j.isprsjprs.2017.03.001."
17
"Yeum, C. M. and Dyke, S. J. (2015). “Vision-based automated crack detection for bridge inspection.” Computer-Aided Civil and Infrastructure Engineering, Wiley, Vol. 30, No. 10, pp. 759-770, https://doi.org/10.1111/mice.12141."