Age prediction with partial facial covering
Covid-19 is still raging around the world, and the behaviour of humans wearing masks in public will continue to exist. The detection or recognition of faces wearing masks has gradually become a popular research direction at this stage. At the same time, age detection is also a forward-looking resear...
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| Format: | Thesis-Master by Coursework |
| Language: | English |
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Nanyang Technological University
2022
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| Online Access: | https://hdl.handle.net/10356/155397 |
| _version_ | 1811679602190319616 |
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| author | Liu, Peixin |
| author2 | Soong Boon Hee |
| author_facet | Soong Boon Hee Liu, Peixin |
| author_sort | Liu, Peixin |
| collection | NTU |
| description | Covid-19 is still raging around the world, and the behaviour of humans wearing masks in public will continue to exist. The detection or recognition of faces wearing masks has gradually become a popular research direction at this stage. At the same time, age detection is also a forward-looking research topic. As more applications or websites collect customers' age information with the permission of customers, intending to push content belonging to their age groups to customers of different ages.
This dissertation explores the feasibility of age prediction for faces wearing masks. The research is based on the Python language environment. The research starts with face detection, extracts the area containing face information in a large environment, and displays the results in the designed GUI interface through the trained age prediction model. Throughout the experiment, I used two improved convolutional neural network models to train three age classifications, and selected the one that best met the criteria and placed it in the display program. |
| first_indexed | 2024-10-01T03:11:46Z |
| format | Thesis-Master by Coursework |
| id | ntu-10356/155397 |
| institution | Nanyang Technological University |
| language | English |
| last_indexed | 2024-10-01T03:11:46Z |
| publishDate | 2022 |
| publisher | Nanyang Technological University |
| record_format | dspace |
| spelling | ntu-10356/1553972023-07-04T17:10:18Z Age prediction with partial facial covering Liu, Peixin Soong Boon Hee School of Electrical and Electronic Engineering EBHSOONG@ntu.edu.sg Engineering::Computer science and engineering::Computing methodologies::Artificial intelligence Covid-19 is still raging around the world, and the behaviour of humans wearing masks in public will continue to exist. The detection or recognition of faces wearing masks has gradually become a popular research direction at this stage. At the same time, age detection is also a forward-looking research topic. As more applications or websites collect customers' age information with the permission of customers, intending to push content belonging to their age groups to customers of different ages. This dissertation explores the feasibility of age prediction for faces wearing masks. The research is based on the Python language environment. The research starts with face detection, extracts the area containing face information in a large environment, and displays the results in the designed GUI interface through the trained age prediction model. Throughout the experiment, I used two improved convolutional neural network models to train three age classifications, and selected the one that best met the criteria and placed it in the display program. Master of Science (Communications Engineering) 2022-02-22T01:24:31Z 2022-02-22T01:24:31Z 2021 Thesis-Master by Coursework Liu, P. (2021). Age prediction with partial facial covering. Master's thesis, Nanyang Technological University, Singapore. https://hdl.handle.net/10356/155397 https://hdl.handle.net/10356/155397 en application/pdf Nanyang Technological University |
| spellingShingle | Engineering::Computer science and engineering::Computing methodologies::Artificial intelligence Liu, Peixin Age prediction with partial facial covering |
| title | Age prediction with partial facial covering |
| title_full | Age prediction with partial facial covering |
| title_fullStr | Age prediction with partial facial covering |
| title_full_unstemmed | Age prediction with partial facial covering |
| title_short | Age prediction with partial facial covering |
| title_sort | age prediction with partial facial covering |
| topic | Engineering::Computer science and engineering::Computing methodologies::Artificial intelligence |
| url | https://hdl.handle.net/10356/155397 |
| work_keys_str_mv | AT liupeixin agepredictionwithpartialfacialcovering |