Multi-label deep learning models for continuous monitoring of road infrastructures-Reference-Cited by-同舟云学术

Multi-label deep learning models for continuous monitoring of road infrastructures

Published:2020-06-26 Issue: Volume: Page:
ISSN:
Container-title:Proceedings of the 13th ACM International Conference on PErvasive Technologies Related to Assistive Environments
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Author:

Protopapadakis Eftychios¹,Katsamenis Iason¹,Doulamis Anastasios¹

Affiliation:

1. University of Athens, Greece

Funder

Horizon 2020 Framework Programme

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/3389189.3397997

Reference50 articles.

1. A. Alfarrarjeh D. Trivedi S. H. Kim and C. Shahabi "A deep learning approach for road damage detection from smartphone images " in 2018 IEEE International Conference on Big Data (Big Data) 2018 pp. 5201--5204. A. Alfarrarjeh D. Trivedi S. H. Kim and C. Shahabi "A deep learning approach for road damage detection from smartphone images " in 2018 IEEE International Conference on Big Data (Big Data) 2018 pp. 5201--5204.

2. 3D reconstruction of road surfaces using an integrated multi-sensory approach

3. R. A. Ferguson etal "Road pavement deterioration inspection system " Sep. 09 2003. R. A. Ferguson et al. "Road pavement deterioration inspection system " Sep. 09 2003.

4. Road inspection using full-wave inversion of far-field ground-penetrating radar data

5. Detecting known and unknown faults in automotive systems using ensemble-based anomaly detection

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