Dr Dimity Miller
Faculty of Science,
School of Computer Science
Artificial Intelligence and Image Processing
Field of Research code, Australian and New Zealand Standard Research Classification (ANZSRC), 2008
- Doctoral Degree (Queensland University of Technology)
- Bachelor of Engineering (Mechatronics, Robotics) (Queensland University of Technology)
- Miller D, Sünderhauf N, Milford M, Dayoub F, (2021) Class Anchor Clustering: A Loss for Distance-based Open Set Recognition, Proceedings of the 2021 Winter Conference on Applications of Computer Vision (WACV '21), pp. 3569-3577.
- Hall D, Dayoub F, Skinner J, Zhang H, Miller D, Corke P, Carneiro G, Angelova A, Sünderhauf N, (2020) Probabilistic object detection: Definition and evaluation, Proceedings of the 2020 IEEE Winter Conference on Applications of Computer Vision (WACV) , pp. 1020-1029.
- Suenderhauf N, Zhang H, Hall D, Dayoub F, Miller D, (2019) Benchmarking sampling-based probabilistic object detectors, Proceedings of the 2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW), pp. 42-45.
- Dayoub F, Milford M, Suenderhauf N, Miller D, (2019) Evaluating merging strategies for sampling-based uncertainty techniques in object detection, Proceedings of the 2019 International Conference on Robotics and Automation (ICRA), pp. 2348-2354.
- Miller D, Nicholson L, Dayoub F, Suenderhauf N, (2018) Dropout sampling for robust object detection in open-set conditions, Proceedings of the 2018 IEEE International Conference on Robotics and Automation (ICRA), pp. 3243-3249.