9 Vision-Based Concrete Crack Detection Using a Convolutional Neural Network 73 References 1. Begg, R.D., et al.: Structural integrity monitoring using digital processing of vibration siqnals. In: Offshore Technology Conference: Offshore Technology Conference (1976) 2. Administration, F.H. [cited 2016 September 21]; Available from: https://www.fhwa.dot.gov/bridge/ 3. Chang, P.C., Flatau, A., Liu, S.: Review paper: health monitoring of civil infrastructure. Struct. Health Monit. 2(3), 257–267 (2003) 4. Phares, B.M., et al.: Reliability of visual bridge inspection. Public Roads. 64(5), (2001) 5. Rice, J.A., et al.: Flexible smart sensor framework for autonomous structural health monitoring. Smart Struct. Syst. 6(5–6), 423–438 (2010) 6. Jang, S., et al.: Structural health monitoring of a cable-stayed bridge using smart sensor technology: deployment and evaluation. Smart Struct. Syst. 6(5–6), 439–459 (2010) 7. Kurata, M., et al.: Internet-enabled wireless structural monitoring systems: development and permanent deployment at the New Carquinez Suspension Bridge. J. Struct. Eng. 139(10), 1688–1702 (2012) 8. Xia, Y., et al.: Temperature effect on vibration properties of civil structures: a literature review and case studies. J. Civ. Struct. Heal. Monit. 2(1), 29–46 (2012) 9. Cornwell, P., et al.: Environmental variability of modal properties. Exp. Tech. 23(6), 45–48 (1999) 10. Behmanesh, I., et al.: Hierarchical Bayesian model updating for structural identification. Mech. Syst. Signal Process. 64, 360–376 (2015) 11. Dorn, C.J., et al.: Automated extraction of mode shapes using motion magnified video and blind source separation. In: Topics in Modal Analysis & Testing. Springer, Cham/Heidelberg (2016) 12. Chen, J.G., et al.: Modal identification of simple structures with high-speed video using motion magnification. J. Sound Vib. 345, 58–71 (2015) 13. Abdel-Qader, I., Abudayyeh, O., Kelly, M.E.: Analysis of edge-detection techniques for crack identification in bridges. J. Comput. Civ. Eng. 17(4), 255–263 (2003) 14. Cha, Y.-J., You, K., Choi, W.: Vision-based detection of loosened bolts using the Hough transform and support vector machines. Autom. Constr. 71, 181–188 (2016) 15. LeCun, Y., et al.: Gradient-based learning applied to document recognition. Proc. IEEE. 86(11), 2278–2324 (1998) 16. LeCun, Y., Bengio, Y., Hinton, G.: Deep learning. Nature. 521(7553), 436–444 (2015) 17. Steinkrau, D., Simard, P.Y., Buck, I.: Using GPUs for machine learning algorithms. In: 8th International Conference on Document Analysis and Recognition. IEEE, Seoul, Korea (2005) 18. Cha, Y.-J., Choi, W.: Deep learning-based crack detection using convolutional neural networks. Comput. Aided Civ. Infrastruct. Eng. 32(3) (2017). doi:10.1111/mice.12263
RkJQdWJsaXNoZXIy MTMzNzEzMQ==