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Brendan

Owheo Building, Room G.31
Tel +64 3 479 8588
Email brendan.mccane@otago.ac.nz

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

Publications

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 Journal - Research Article

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 Journal - Research Article

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 Journal - Research Article

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 Journal - Research Article

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

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