Small Face Detection with Deep Learning Approaches
This thesis considers small face detection in uncontrolled environments and develops robust deep learning approaches for this challenging problem. A novel multi-scale face detector is developed by integrating novel anchor design, efficient regression loss and additional detection layers. Several mul...
| Main Author: | |
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| Format: | Thesis |
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Curtin University
2021
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| Online Access: | http://hdl.handle.net/20.500.11937/86208 |
| _version_ | 1848764791485628416 |
|---|---|
| author | Tuli, Sabrina Hoque |
| author_facet | Tuli, Sabrina Hoque |
| author_sort | Tuli, Sabrina Hoque |
| building | Curtin Institutional Repository |
| collection | Online Access |
| description | This thesis considers small face detection in uncontrolled environments and develops robust deep learning approaches for this challenging problem. A novel multi-scale face detector is developed by integrating novel anchor design, efficient regression loss and additional detection layers. Several multi-scale dense convolutional networks are developed to boost up the detection of small faces. Experimental results on public face databases demonstrate that the proposed methods outperform the state-of-the-art methods (e.g. YOLOv3) for detection of small faces. |
| first_indexed | 2025-11-14T11:24:58Z |
| format | Thesis |
| id | curtin-20.500.11937-86208 |
| institution | Curtin University Malaysia |
| institution_category | Local University |
| last_indexed | 2025-11-14T11:24:58Z |
| publishDate | 2021 |
| publisher | Curtin University |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | curtin-20.500.11937-862082021-10-26T00:12:02Z Small Face Detection with Deep Learning Approaches Tuli, Sabrina Hoque This thesis considers small face detection in uncontrolled environments and develops robust deep learning approaches for this challenging problem. A novel multi-scale face detector is developed by integrating novel anchor design, efficient regression loss and additional detection layers. Several multi-scale dense convolutional networks are developed to boost up the detection of small faces. Experimental results on public face databases demonstrate that the proposed methods outperform the state-of-the-art methods (e.g. YOLOv3) for detection of small faces. 2021 Thesis http://hdl.handle.net/20.500.11937/86208 Curtin University fulltext |
| spellingShingle | Tuli, Sabrina Hoque Small Face Detection with Deep Learning Approaches |
| title | Small Face Detection with Deep Learning
Approaches |
| title_full | Small Face Detection with Deep Learning
Approaches |
| title_fullStr | Small Face Detection with Deep Learning
Approaches |
| title_full_unstemmed | Small Face Detection with Deep Learning
Approaches |
| title_short | Small Face Detection with Deep Learning
Approaches |
| title_sort | small face detection with deep learning
approaches |
| url | http://hdl.handle.net/20.500.11937/86208 |