Full metadata record
| DC Field | Value | Language |
|---|---|---|
| dc.contributor.author | Hyun, Eugin | - |
| dc.contributor.author | Jin, YoungSeok | - |
| dc.contributor.author | Bae, Jieun | - |
| dc.contributor.author | Park, Chi-Ho | - |
| dc.date.accessioned | 2024-01-04T16:10:22Z | - |
| dc.date.available | 2024-01-04T16:10:22Z | - |
| dc.date.created | 2023-09-15 | - |
| dc.date.issued | 2023-06-23 | - |
| dc.identifier.isbn | 9798350311143 | - |
| dc.identifier.issn | 2577-2465 | - |
| dc.identifier.uri | http://hdl.handle.net/20.500.11750/47570 | - |
| dc.description.abstract | In this paper, we propose a passenger monitoring scheme using a 60GHz FMCW radar for in-cabin applications. Based on the 2D images using cloud point, we employed a 2D deep learning method. We found an average recognition rate at 96 %, which was one to five occupants in a vehicle. © 2023 IEEE. | - |
| dc.language | English | - |
| dc.publisher | Institute of Electrical and Electronics Engineers Inc. | - |
| dc.relation.ispartof | 2023 IEEE 97th Vehicular Technology Conference (VTC2023-Spring) | - |
| dc.title | Machine Learning based In-Cabin Radar System for Passenger Monitoring System | - |
| dc.type | Conference Paper | - |
| dc.identifier.doi | 10.1109/VTC2023-Spring57618.2023.10200306 | - |
| dc.identifier.wosid | 001054797201132 | - |
| dc.identifier.scopusid | 2-s2.0-85169799227 | - |
| dc.identifier.bibliographicCitation | 97th IEEE Vehicular Technology Conference (VTC-Spring) | - |
| dc.identifier.url | https://events.vtsociety.org/vtc2023-spring/wp-content/uploads/sites/36/2023/06/vtc2023spring_program-living-main1.pdf | - |
| dc.citation.conferenceDate | 2023-06-20 | - |
| dc.citation.conferencePlace | IT | - |
| dc.citation.conferencePlace | Florence, ITALY | - |
| dc.citation.title | 97th IEEE Vehicular Technology Conference (VTC-Spring) | - |
- Files in This Item:
-
There are no files associated with this item.
Items in Repository are protected by copyright, with all rights reserved, unless otherwise indicated.