MFCC Delta–Delta Energy Feature Extraction for Clustering of Road Surface Types-Reference-Cited by-同舟云学术

MFCC Delta–Delta Energy Feature Extraction for Clustering of Road Surface Types

Published:2022-02-22 Issue:3 Volume:16 Page:631-646
ISSN:1996-6814
Container-title:International Journal of Pavement Research and Technology
language:en
Short-container-title:Int. J. Pavement Res. Technol.

Author:

Jawale Anupama^ORCID,Magar Ganesh

Publisher

Springer Science and Business Media LLC

Subject

Mechanics of Materials,Civil and Structural Engineering

Link

https://link.springer.com/content/pdf/10.1007/s42947-022-00153-2.pdf

Reference45 articles.

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2. Carlos, R., Gonzalez, L. C., Wahlstrom, J., Cornejo, R., & Martinez, F. (2019). Becoming smarter at characterizing potholes and speed bumps from smartphone data—introducing a second-generation inference problem. IEEE Transactions on Mobile Computing. https://doi.org/10.1109/TMC.2019.2947443

3. Eriksson, J., Girod, L., Hull, B., Newton, R., Madden, S., & Balakrishnan, H. (2008). The pothole patrol: using a mobile sensor network for road surface monitoring, in Proceeding of the 6th international conference on Mobile systems, applications, and services—MobiSys ’08, p. 29. https://doi.org/10.1145/1378600.1378605

4. Fan, R., Ozgunalp, U., Hosking, B., Liu, M., & Pitas, I. (2020). Pothole detection based on disparity transformation and road surface modeling. IEEE Transactions on Image Processing., 29, 897–908. https://doi.org/10.1109/TIP.2019.2933750

5. “Manual for Design, Construction and maintenance of Graval Road, in Manual for Design, Construction and maintenance of Graval Road, Indian Roads Congress, 2008