Accurate detection of driver urgency using state-of-the-art supervised and unsupervised classification algorithms
This study is to determine the factors affect the accuracy of detection of driver face urgency situations under 2 different of State-of-the-Art classification algorithms, which are supervised and unsupervised.
| Main Author: | |
|---|---|
| Other Authors: | |
| Format: | Final Year Project (FYP) |
| Language: | English |
| Published: |
Nanyang Technological University
2023
|
| Subjects: | |
| Online Access: | https://hdl.handle.net/10356/167924 |
| _version_ | 1811692189754851328 |
|---|---|
| author | Kong,Yuanjie |
| author2 | Su Rong |
| author_facet | Su Rong Kong,Yuanjie |
| author_sort | Kong,Yuanjie |
| collection | NTU |
| description | This study is to determine the factors affect the accuracy of detection of driver face urgency situations under 2 different of State-of-the-Art classification algorithms, which are supervised and unsupervised. |
| first_indexed | 2024-10-01T06:31:50Z |
| format | Final Year Project (FYP) |
| id | ntu-10356/167924 |
| institution | Nanyang Technological University |
| language | English |
| last_indexed | 2024-10-01T06:31:50Z |
| publishDate | 2023 |
| publisher | Nanyang Technological University |
| record_format | dspace |
| spelling | ntu-10356/1679242023-07-07T15:45:40Z Accurate detection of driver urgency using state-of-the-art supervised and unsupervised classification algorithms Kong,Yuanjie Su Rong School of Electrical and Electronic Engineering RSu@ntu.edu.sg Engineering::Electrical and electronic engineering This study is to determine the factors affect the accuracy of detection of driver face urgency situations under 2 different of State-of-the-Art classification algorithms, which are supervised and unsupervised. Bachelor of Engineering (Electrical and Electronic Engineering) 2023-06-05T07:23:54Z 2023-06-05T07:23:54Z 2023 Final Year Project (FYP) Kong, Y. (2023). Accurate detection of driver urgency using state-of-the-art supervised and unsupervised classification algorithms. Final Year Project (FYP), Nanyang Technological University, Singapore. https://hdl.handle.net/10356/167924 https://hdl.handle.net/10356/167924 en P1047-212 application/pdf Nanyang Technological University |
| spellingShingle | Engineering::Electrical and electronic engineering Kong,Yuanjie Accurate detection of driver urgency using state-of-the-art supervised and unsupervised classification algorithms |
| title | Accurate detection of driver urgency using state-of-the-art supervised and unsupervised classification algorithms |
| title_full | Accurate detection of driver urgency using state-of-the-art supervised and unsupervised classification algorithms |
| title_fullStr | Accurate detection of driver urgency using state-of-the-art supervised and unsupervised classification algorithms |
| title_full_unstemmed | Accurate detection of driver urgency using state-of-the-art supervised and unsupervised classification algorithms |
| title_short | Accurate detection of driver urgency using state-of-the-art supervised and unsupervised classification algorithms |
| title_sort | accurate detection of driver urgency using state of the art supervised and unsupervised classification algorithms |
| topic | Engineering::Electrical and electronic engineering |
| url | https://hdl.handle.net/10356/167924 |
| work_keys_str_mv | AT kongyuanjie accuratedetectionofdriverurgencyusingstateoftheartsupervisedandunsupervisedclassificationalgorithms |