DG-SegNet: A depth-guided RGB-D semantic segmentation framework for emergency escape ramps toward traffic accident prevention.
- DOI
- 10.1080/15389588.2026.2713113
- Published
- 2026 Sep 14
- Container
- Traffic injury prevention
- Publisher
- Not recorded
- Open access
- unknown
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Cite this work
BibTeX
@article{allodium:10.1080/15389588.2026.2713113,
title = {DG-SegNet: A depth-guided RGB-D semantic segmentation framework for emergency escape ramps toward traffic accident prevention.},
author = {Hu Z and Hao Y and Li J and Li G and Wang L},
year = {2026},
journal = {Traffic injury prevention},
doi = {10.1080/15389588.2026.2713113},
url = {https://doi.org/10.1080/15389588.2026.2713113}
}RIS
TY - JOUR TI - DG-SegNet: A depth-guided RGB-D semantic segmentation framework for emergency escape ramps toward traffic accident prevention. AU - Hu Z AU - Hao Y AU - Li J AU - Li G AU - Wang L PY - 2026 JO - Traffic injury prevention DO - 10.1080/15389588.2026.2713113 UR - https://doi.org/10.1080/15389588.2026.2713113 ER -
APA
Z, H., Y, H., J, L., G, L., & L, W. (2026). DG-SegNet: A depth-guided RGB-D semantic segmentation framework for emergency escape ramps toward traffic accident prevention.. Traffic injury prevention. https://doi.org/10.1080/15389588.2026.2713113
Source records
- pubmed · retrieved 2026-09-26T12:36:33.922Z