Time-Series Classification for Industrial Applications: Road Surface Damage Detection Use Case

Author:

Burnaev E. V.

Publisher

Pleiades Publishing Ltd

Subject

Electrical and Electronic Engineering,Condensed Matter Physics,Radiation,Electronic, Optical and Magnetic Materials

Reference22 articles.

1. R. Fan and M. Liu, “Road damage detection based on unsupervised disparity map segmentation,” IEEE Trans. Intell. Transp. Syst., 1–6 (2019).

2. Shen-En Chen, Wanqiu Liu, Haitao Bian, and Ben Smith, “3D LiDAR scans for bridge damage evaluations,” Forensic Eng., 487–495 (2012).

3. Gunawan Fergyanto, “Detecting road damages by using gyroscope sensor,” ICIC Express Lett. 12, 1089–1098 (2018).

4. S. Sattar, S. Li, and M. Chapman, “Road surface monitoring using smartphone sensors: A review,” Sensors, Basel 18 (11), (2018).

5. A. Alfarrarjeh, D. Trivedi, S. H. Kim, and C. Shahabi, “A deep learning approach for road damage detection from smartphone mages” in Proc. IEEE Int. Conf. on Big Data (Big Data), Seattle, WA, USA, Dec. 10–13, 2018 (IEEE, New York, 2018, pp. 5201–5204.

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