최소 단어 이상 선택하여야 합니다.
최대 10 단어까지만 선택 가능합니다.
다음과 같은 기능을 한번의 로그인으로 사용 할 수 있습니다.
NTIS 바로가기Journal of the Korean Recycled Construction Resources Institute = 한국건설순환자원학회 논문집, v.9 no.3, 2021년, pp.303 - 310
지봉준 (포항공과대학교 산업경영공학과)
Cracks in bridges are important factors that indicate the condition of bridges and should be monitored periodically. However, a visual inspection conducted by a human expert has problems in cost, time, and reliability. Therefore, in recent years, researches to apply a deep learning model are started...
Dorafshan, S., Maguire, M. (2017). Autonomous detection of concrete cracks on bridge decks and fatigue cracks on steel members, Digital Imaging, 33-44.
Gao, X., Deng, F., Yue, X. (2020). Data augmentation in fault diagnosis based on the Wasserstein generative adversarial network with gradient penalty, Neurocomputing, 396, 487-494.
Goodfellow, I., Pouget-Abadie, J., Mirza, M., Xu, B., Warde-Farley, D., Ozair, S., Courville, A., Bengio, Y. (2014). Generative adversarial networks, Proceedings of the International Conference on Neural Information Processing Systems(NIPS 2014), 2672-2680.
Han, C., Rundo, L., Araki, R., Furukawa, Y., Mauri, G., Nakayama, H., Hayashi, H. (2020). Infinite brain MR images: PGGAN-based data augmentation for tumor detection, In Neural Approaches to Dynamics of Signal Exchanges, 291-303.
He, H., Garcia, E.A. (2009). Learning from imbalanced data, IEEE Transactions on Knowledge and Data Engineering, 21(9), 1263-1284.
Lee, B.J., Shin, J.I., Park, C.H. (2008). Development of image processing program to inspect concrete bridges, Proceedings of the Korea Concrete Institute Conference, 189-192 [In Korean].
Lim, S.K., Loo, Y., Tran, N.T., Cheung, N.M., Roig, G., Elovici, Y. (2018). Doping: Generative data augmentation for unsupervised anomaly detection with gan, IEEE International Conference on Data Mining (ICDM) 1122-1127.
Lorencin, I., Baressi Segota, S., Andelic, N., Mrzljak, V., Cabov, T., Spanjol, J., Car, Z. (2021). On urinary bladder cancer diagnosis: Utilization of deep convolutional generative adversarial networks for data augmentation, Biology, 10(3), 175.
Mok, T.C., Chung, A.C. (2018). Learning data augmentation for brain tumor segmentation with coarse-to-fine generative adversarial networks, International MICCAI Brainlesion Workshop, 70-80.
Nishikawa, T., Yoshida, J., Sugiyama, T., Fujino, Y. (2012). Concrete crack detection by multiple sequential image filtering, Computer-Aided Civil and Infrastructure Engineering, 27(1), 29-47.
Ortego, P., Diez-Olivan, A., Del Ser, J., Sierra, B. (2020) Data augmentation for industrial prognosis using generative adversarial networks, International Conference on Intelligent Data Engineering and Automated Learning, 113-122.
Peres, R.S., Azevedo, M., Araujo, S.O., Guedes, M., Miranda, F., Barata, J. (2021). Generative adversarial networks for data augmentation in structural adhesive inspection, Applied Sciences, 11(7), 3086.
Ramponi, G., Protopapas, P., Brambilla, M., Janssen, R. (2018). T-cgan: conditional generative adversarial network for data augmentation in noisy time series with irregular sampling, arXiv preprint arXiv:1811.08295.
Simonyan, K., Zisserman, A. (2014). Very deep convolutional networks for large-scale image recognition, arXiv preprint arXiv:1409.1556.
Yamaguchi, T., Hashimoto, S. (2010). Fast crack detection method for large-size concrete surface images using percolation-based image processing, Machine Vision and Applications, 21(5), 797-809.
Yang, F., Zhang, L., Yu, S., Prokhorov, D., Mei, X., Ling, H. (2019). Feature pyramid and hierarchical boosting network for pavement crack detection, IEEE Transactions on Intelligent Transportation Systems, 21(4), 1525-1535.
Zhu, Z., German, S., Brilakis, I. (2011). Visual retrieval of concrete crack properties for automated post-earthquake structural safety evaluation, Automation in Construction, 20(7), 874-883.
Zou, Q., Zhang, Z., Li, Q., Qi, X., Wang, Q., Wang, S. (2018). Deepcrack: Learning hierarchical convolutional features for crack detection, IEEE Transactions on Image Processing, 28(3), 1498-1512.
*원문 PDF 파일 및 링크정보가 존재하지 않을 경우 KISTI DDS 시스템에서 제공하는 원문복사서비스를 사용할 수 있습니다.
오픈액세스 학술지에 출판된 논문
※ AI-Helper는 부적절한 답변을 할 수 있습니다.