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Owheo Building, Room G.31
Tel +64 3 479 8588

My research interests include computer vision, pattern recognition, machine learning, biomedical imaging, and robotics. My current research focuses on theoretical understanding of the effectiveness of deep networks, and self-learning for robots.

I also have an interest in computer graphics and participate in the computer graphics group here at the University of Otago.

My background is in Computer Science and I completed my undergraduate studies and PhD at James Cook University of North Queensland in Australia. My PhD was entitled "Learning to Recognise 3D Objects from 2D Intensity Images", which I completed in February 1996. I then held a temporary position as a lecturer at James Cook University, before taking up a position in February 1997 as a lecturer with the Computer Science Department here at Otago University.

For more information see my research pages


Liu, J., McCane, B., & Mills, S. (2024). Learning to explore by reinforcement over high-level options. Machine Vision & Applications, 35, 6. doi: 10.1007/s00138-023-01492-1

Xu, H., Szymanski, L., & McCane, B. (2023). VASE: Variational assorted surprise exploration for reinforcement learning. IEEE Transactions on Neural Networks & Learning Systems, 34(3), 1243-1252. doi: 10.1109/TNNLS.2021.3105140

Liu, J., Mills, S., & McCane, B. (2022). RocNet: Recursive octree network for efficient 3D processing. Computer Vision & Image Understanding, 224, 103555. doi: 10.1016/j.cviu.2022.103555

Bennani, H., McCane, B., & Cornwall, J. (2022). Three-dimensional reconstruction of in vivo human lumbar spine from biplanar radiographs. Computerized Medical Imaging & Graphics, 96, 102011. doi: 10.1016/j.compmedimag.2021.102011

Szymanski, L., McCane, B., & Atkinson, C. (2022). Conceptual complexity of neural networks. Neurocomputing, 469, 52-64. doi: 10.1016/j.neucom.2021.10.063

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