과제정보
이 논문은 2023년도 정부(과학기술정보통신부)의 재원으로 정보통신기획평가원의 지원을 받아 수행된 연구임 (No. RS-2023-00233470, 인공신경망 이미지 분석을 이용한 레일표면손상 진단시스템 개발)
참고문헌
- J.Y Choi, J.M. Han, Y.K. Kim, "Correlation Analysis of Rail Surface Defects and Rail Internal Cracks", The Journal of the Convergence on Culture Technology (JCCT), Vol. 10, No. 1, pp.585-591, 2024. http://dx.doi.org/10.17703/JCCT.2024.10.1.585
- J.Y. Choi, H.S. Kim, K.S. Han, C.J. Jang, J.S. Chung "Damage Evaluation of Track Components for Sleeper Floating Track System in Urban Transit", The Journal of the Convergence on Culture Technology (JCCT), Vol. 5, No. 4, pp.387-394, 2019. https://doi.org/10.17703/JCCT.2021.7.3.517
- L. Perez and J. Wang, "The effectiveness of data augmentation in image classification using deep learning," arXiv preprint arXiv:1712.04621, 2017.
- S. Ren, K. He, G. Ross, and S. Jian, "Faster r-cnn: Towards real-time object detection with region proposal networks", Advances in Neural Information Processing Systems, Vol. 28, pp. 91-99, 2015.
- G. M. Jog, C. Koch, M. Golparvar-Fard, and I. Brilakis, "Pothole properties measurement through visual 2D recognition and 3D reconstruction", International Conference on Computing in Civil Engineering, pp. 553-560, 2012.
- E. Buza, S. Omanovic, and A. Huseinovic, "A pothole detection with image processing and spectral clustering", Proc. the 2nd International Conference on Information Technology and Computer Networks, Antalya, Turkeys, pp. 48-53, 2013.
- A. Mednis, G. Strazdins, R. Zviedris, G. Kanonirs, and L. Selavo, "Real time pothole detection using Android smartphones with accelerometers", Proc. IEEE International Conference on Distributed Computing in Sensor Systems and Workshops, Barcelona, Spain. 2011.
- T.H. Kim, S.K. Ryu, "Review and analysis of pothole detection methods", Journal of Emerging Trends in Computing and Information Sciences, Vol. 5, No. 8, pp. 603-608. 2014.
- M.K. Lee, K.S. Seo, "Comparison of Region-based CNN Methods for Defects Detection on Metal Surface", The Transactions of the Korean Institute of Electrical Engineers, Vol. 67, No. 7, PP.865-870, 2018
- D.H. Seol, J.H. Oh, H.J. Kim, "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, 2020