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A deep learning framework for road marking extraction, classification and completion from mobile laser scanning point clouds
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“FL decision support systems were applied to problems such as routing, fraud prevention, and mobility on-demand (Liyanage et al., 2019; Wen et al., 2019).”
From Artificial intelligence for sustainability: Challenges, opportunities, and a research agenda (2020) · cites this paper as Wen et al., 2019
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Metadata
- Authors
- Wen, C., Sun, X., Li, J., Wang, C., Guo, Y., & Habib, A.
- Affiliations
- Xiamen University (CN)
- University of Waterloo (CA)
- Purdue University West Lafayette (US)
- Corresponding author
- Li, Jonathan
- Venue
- ISPRS Journal of Photogrammetry and Remote Sensing
- Publisher
- Elsevier BV
- Published
- 2019-01
- Volume
- 147
- Pages
- 178-192
- ISSN
- 0924-2716 (ISSN-L)
- OpenAlex
- W2902218628
- Cited by
- 158
- References
- 48
- Citations by year
- 2026: 12 · 2025: 12 · 2024: 18 · 2023: 23 · 2022: 27 · 2021: 22 · 2020: 24 · 2019: 20
- FWCI
- 13.22
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- ISPRS Journal of Photogrammetry and Remote Sensing (publishedVersion)
- Funders
- National Natural Science Foundation of China (41471379, 61771413, U1605254, 20720170047)
- Fundamental Research Funds for the Central Universities
- Topics
- Physical Sciences › Computer Science › Computer Vision and Pattern Recognition › Automated Road and Building Extraction
- Physical Sciences › Engineering › Civil and Structural Engineering › Infrastructure Maintenance and Monitoring
- Physical Sciences › Engineering › Automotive Engineering › Autonomous Vehicle Technology and Safety
- Keywords
- mobile laser scanning, point clouds, autonomous vehicles, HD maps, multi-scale clustering, hierarchical classification, generative adversarial networks
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