Masked face recognition
Biometric security is a type of security that verifies people's physical or behavioural features to identify them. One of them being face recognition, which is a technology that is capable of matching human faces to a database of faces. There are several existing deep learning models used for f...
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Nanyang Technological University
2021
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| Online Access: | https://hdl.handle.net/10356/153275 |
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sg-ntu-dr.10356-1532752021-11-17T04:45:29Z Masked face recognition Sim, Song Qin Lin Weisi School of Computer Science and Engineering WSLin@ntu.edu.sg Engineering::Computer science and engineering Biometric security is a type of security that verifies people's physical or behavioural features to identify them. One of them being face recognition, which is a technology that is capable of matching human faces to a database of faces. There are several existing deep learning models used for face recognition. In this project, we are going to develop an alternative approach to this task. We will build our model based on a state-of-the-art model, and apply the attention mechanism. The accuracy of our model will be compared with existing face recognition models to evaluate its effectiveness. Bachelor of Engineering (Computer Engineering) 2021-11-17T04:45:29Z 2021-11-17T04:45:29Z 2021 Final Year Project (FYP) Sim, S. Q. (2021). Masked face recognition. Final Year Project (FYP), Nanyang Technological University, Singapore. https://hdl.handle.net/10356/153275 https://hdl.handle.net/10356/153275 en SCSE20-0934 application/pdf Nanyang Technological University |
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Singapore Singapore |
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Engineering::Computer science and engineering |
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Engineering::Computer science and engineering Sim, Song Qin Masked face recognition |
| description |
Biometric security is a type of security that verifies people's physical or behavioural features to identify them. One of them being face recognition, which is a technology that is capable of matching human faces to a database of faces. There are several existing deep learning models used for face recognition. In this project, we are going to develop an alternative approach to this task. We will build our model based on a state-of-the-art model, and apply the attention mechanism. The accuracy of our model will be compared with existing face recognition models to evaluate its effectiveness. |
| author2 |
Lin Weisi |
| author_facet |
Lin Weisi Sim, Song Qin |
| format |
Final Year Project |
| author |
Sim, Song Qin |
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Sim, Song Qin |
| title |
Masked face recognition |
| title_short |
Masked face recognition |
| title_full |
Masked face recognition |
| title_fullStr |
Masked face recognition |
| title_full_unstemmed |
Masked face recognition |
| title_sort |
masked face recognition |
| publisher |
Nanyang Technological University |
| publishDate |
2021 |
| url |
https://hdl.handle.net/10356/153275 |
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1718368034816524288 |