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https://hdl.handle.net/10356/167924| Title: | Accurate detection of driver urgency using state-of-the-art supervised and unsupervised classification algorithms | Authors: | Kong,Yuanjie | Keywords: | Engineering::Electrical and electronic engineering | Issue Date: | 2023 | Publisher: | Nanyang Technological University | Source: | 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 | Project: | P1047-212 | Abstract: | 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. | URI: | https://hdl.handle.net/10356/167924 | Schools: | School of Electrical and Electronic Engineering | Fulltext Permission: | restricted | Fulltext Availability: | With Fulltext |
| Appears in Collections: | EEE Student Reports (FYP/IA/PA/PI) |
Files in This Item:
| File | Description | Size | Format | |
|---|---|---|---|---|
| FYP_Report final -Kong Yuanjie.pdf Restricted Access | 1.55 MB | Adobe PDF | View/Open |
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