Development of Open Set Recognition-based Multiple Damage Recognition Model for Bridge Structure Damage Detection |
Kim, Young-Nam
(Department of Electrical and Computer Engineering, Sungkyunkwan University, Advanced Institute of Convergence Technology)
Cho, Jun-Sang (Korea Expressway Corporation) Kim, Jun-Kyeong (Advanced Institute of Convergence Technology) Kim, Moon-Hyun (Sungkyunkwan University) Kim, Jin-Pyung (Advanced Institute of Convergence Technology) |
1 | Park, J. M., Kim, H. S., Shin, D. H., Park, M. S. and Kim, S. H. (2019). "A study on machine learning algorithm suitable for automatic crack detection in wall-climbing robot." Kips Transactions on Software and Data Engineering, Vol. 8, No. 11, pp. 449-456. DOI |
2 | Sun, X., Li, X., Ren, K. and Song, J. (2019). "Solving the defect in application of compact abating probability to convolutional neural network based open set recognition." 2019 IEEE 31st International Conference on Tools with Artificial Intelligence, ICTAI, Portland, USA. |
3 | Bendale, A. and Boult, T. E. (2016). "Towards open set deep networks." Proceedings of the IEEE Conference on Computer Vision and pattern Recognition, Las Vegas, Nevada, USA, pp. 1563-1572. |
4 | Liu, Y., Tang, Y., Zhang, L., Liu, L., Song, M., Gong, K., Peng, Y., Hou, J. and Jiang, T. (2020). "Hyperspectral open set classification with unknown classes rejection towards deep networks." International Journal of Remote Sensing, Vol. 41, No. 16, pp. 6355-6383. DOI |
5 | Cha, Y. J., Choi, W. R. and Buyukozturk, O. (2017). "Deep learning-based crack damage detection using convolutional neural networks." Computer-Aided Civil and Infrastructure Engineering, Vol. 32, No. 5, pp. 361-378. DOI |
6 | Fisher, R. A. and Tippett, L. H. C. (1928). "Limiting forms of the frequency distribution of the largest or smallest member of a sample." Mathematical Proceedings of the Cambridge Philosophical Society, Cambridge University Press, Vol. 24. No. 2, pp. 180-190. |
7 | Jenkinson, A. F. (1955). "The frequency distribution of the annual maximum (or minimum) values of meteorological elements." Quarterly Journal of the Royal Meteorological Society, Vol. 81, No. 348, pp. 158-171. DOI |
8 | Kim, S. M., Sohn, J. M. and Kim, D. S. (2020). "A method for concrete crack detection using U-Net based image inpainting technique." Journal of The Korea Society of Computer and Information, Vol. 25, No. 10, pp. 35-42. DOI |
9 | Korea Expressway Corporation Research Institute (KECRI) (2015). Prediction model for long-term maintenance costs of highway bridges. |
10 | Korea Expressway Corporation Research Institute (KECRI) (2020). Image-based inspection techniques of bridge for seoul-sejong expressway. |
11 | Neal, L., Olson, M., Fern, X., Wong, W. K. and Li, F. (2018). "Open set learning with counterfactual images." Proceedings of the European Conference on Computer Vision, ECCV, Munich, Germany, pp. 1-16. |
12 | Ozgenel, C. F. (2019). "Concrete crack images for classification." Mendeley Data, Version 2, DOI: 10.17632/5y9wdsg2zt.2. DOI |
13 | LeCun, Y., Bottou, L., Bengio, Y. and Haffner, P. (1998). "Gradient-based learning applied to document recognition." Proceedings of the IEEE, Vol. 86, No. 11, pp. 2278-2324. DOI |
14 | Bendale, A. and Boult, T. E. (2015). "Towards open world recognition." Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, Boston, Massachusetts, USA, pp. 1893-1902. |
15 | Nguyen, A., Yosinski, J. and Clune, J. (2015). "Deep neural networks are easily fooled: High confidence predictions for unrecognizable images." Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, Boston, Massachusetts, USA, pp. 427-436. |
16 | Scheirer, W. J., Rocha, A. R., Sapkota, A. and Boult, T. E. (2012). "Toward open set recognition." IEEE Transactions on Pattern Analysis and Machine Intelligence, Vol. 35, No. 7, pp. 1757-1772. DOI |
17 | Scheirer, W. J., Rocha, A., Micheals, R. J. and Boult, T. E. (2011). "Meta-recognition: The theory and practice of recognition score analysis." IEEE Transactions on Pattern Analysis and Machine Intelligence, Vol. 33, No. 8, pp. 1689-1695. DOI |
18 | Seol, D. H., Oh, J. H. and Kim, H. J. (2020). "Comparison of deep learning-based CNN models for crack detection." Journal of The Architectural Institute of Korea Structure & Construction, Vol. 36, No. 3, pp. 113-120. |
19 | Simonyan, K. and Zisserman, A. (2014). "Very deep convolutional networks for large-scale image recognition." arXiv preprint arXiv:1409.1556. |
20 | Scherreik, M. D. and Rigling, B. D. (2016). "Open set recognition for automatic target classification with rejection." IEEE Transactions on Aerospace and Electronic Systems, Vol. 52, No. 2, pp. 632-642. DOI |