Euclidean consistency-driven dual-layer information fusion framework for UAV-based traffic accident scene reconstruction.
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| Title: | Euclidean consistency-driven dual-layer information fusion framework for UAV-based traffic accident scene reconstruction. |
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| Authors: | Xie Z; College of Civil Engineering, Nanjing forestry University, Nanjing, China.; Jiangsu Highway Intelligent Detection and Low-Carbon Maintenance Engineering Research Center, Nanjing Forestry University, Nanjing, Jiangsu, China., Xia W; College of Civil Engineering, Nanjing forestry University, Nanjing, China.; Jiangsu Highway Intelligent Detection and Low-Carbon Maintenance Engineering Research Center, Nanjing Forestry University, Nanjing, Jiangsu, China.; Department of Civil and Environmental Engineering, National University of Singapore, Singapore, Singapore., He C; Investigation College, Nanjing Police College, Nanjing, Jiangsu, China., Qiu T; Investigation College, Nanjing Police College, Nanjing, Jiangsu, China. |
| Source: | PloS one [PLoS One] 2026 Jun 24; Vol. 21 (6), pp. e0350987. Date of Electronic Publication: 2026 Jun 24 (Print Publication: 2026). |
| Publication Type: | Journal Article |
| Journal Info: | Publisher: Public Library of Science Country of Publication: United States NLM ID: 101285081 Publication Model: eCollection Cited Medium: Internet ISSN: 1932-6203 (Electronic) Linking ISSN: 19326203 NLM ISO Abbreviation: PLoS One Subsets: MEDLINE |
| Database: | MEDLINE Ultimate |
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| ISSN: | 1932-6203 |
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| DOI: | 10.1371/journal.pone.0350987 |
