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.
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| Format: | Final Year Project |
| Language: | English |
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Nanyang Technological University
2023
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| Online Access: | https://hdl.handle.net/10356/167924 |
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| Institution: | Nanyang Technological University |
| Language: | English |
| Summary: | 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. |
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