Human behaviour recognition
This project aims to explore different methodologies in action recognition, including state-of-the-art techniques. The report presents the findings of the survey on video action recognition models and datasets, as well as the latest advancements in action recognition models and large-scale multi-vie...
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| Format: | Final Year Project (FYP) |
| Language: | English |
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Nanyang Technological University
2023
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| Online Access: | https://hdl.handle.net/10356/167656 |
| _version_ | 1826119350027812864 |
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| author | Ng, Cheryl Si Ying |
| author2 | Tan Yap Peng |
| author_facet | Tan Yap Peng Ng, Cheryl Si Ying |
| author_sort | Ng, Cheryl Si Ying |
| collection | NTU |
| description | This project aims to explore different methodologies in action recognition, including state-of-the-art techniques. The report presents the findings of the survey on video action recognition models and datasets, as well as the latest advancements in action recognition models and large-scale multi-view datasets. Additionally, the report also discusses the application of transfer learning, which is a machine learning technique that uses the knowledge gained from one domain to improve the performance of a model in another domain. |
| first_indexed | 2024-10-01T04:58:52Z |
| format | Final Year Project (FYP) |
| id | ntu-10356/167656 |
| institution | Nanyang Technological University |
| language | English |
| last_indexed | 2024-10-01T04:58:52Z |
| publishDate | 2023 |
| publisher | Nanyang Technological University |
| record_format | dspace |
| spelling | ntu-10356/1676562023-07-07T16:23:10Z Human behaviour recognition Ng, Cheryl Si Ying Tan Yap Peng School of Electrical and Electronic Engineering EYPTan@ntu.edu.sg Engineering::Electrical and electronic engineering This project aims to explore different methodologies in action recognition, including state-of-the-art techniques. The report presents the findings of the survey on video action recognition models and datasets, as well as the latest advancements in action recognition models and large-scale multi-view datasets. Additionally, the report also discusses the application of transfer learning, which is a machine learning technique that uses the knowledge gained from one domain to improve the performance of a model in another domain. Bachelor of Engineering (Electrical and Electronic Engineering) 2023-05-30T08:36:28Z 2023-05-30T08:36:28Z 2023 Final Year Project (FYP) Ng, C. S. Y. (2023). Human behaviour recognition. Final Year Project (FYP), Nanyang Technological University, Singapore. https://hdl.handle.net/10356/167656 https://hdl.handle.net/10356/167656 en A3234-221 application/pdf Nanyang Technological University |
| spellingShingle | Engineering::Electrical and electronic engineering Ng, Cheryl Si Ying Human behaviour recognition |
| title | Human behaviour recognition |
| title_full | Human behaviour recognition |
| title_fullStr | Human behaviour recognition |
| title_full_unstemmed | Human behaviour recognition |
| title_short | Human behaviour recognition |
| title_sort | human behaviour recognition |
| topic | Engineering::Electrical and electronic engineering |
| url | https://hdl.handle.net/10356/167656 |
| work_keys_str_mv | AT ngcherylsiying humanbehaviourrecognition |