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dc.contributor.authorTuli, Sabrina Hoque
dc.contributor.supervisorWan-Quan Liuen_US
dc.contributor.supervisorLing Lien_US
dc.contributor.supervisorSenjian Anen_US

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.

dc.publisherCurtin Universityen_US
dc.titleSmall Face Detection with Deep Learning Approachesen_US
curtin.departmentSchool of Electrical Engineering, Computing and Mathematical Sciencesen_US
curtin.accessStatusOpen accessen_US
curtin.facultyScience and Engineeringen_US

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