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  1. Australian Robotics and Automation Association. Dec 2013. "Towards Bio-inspired Place Recognition over Multiple Spatial Scales," Zetao Chen, Adam Jacobson, Ugur Murat Erdem, Michael Hasselmo and Michael Milford. This paper was a collaborative paper led by QUT with neuroscientists at Boston University. The award has been established in memory of ...

  2. Multi-Technique Sequential Information Consistency For Dynamic Visual Place Recognition In Changing Environments. CoRR abs/2401.08263 ( 2024) [i120] Gokul B. Nair, Michael Milford, Tobias Fischer: Enhancing Visual Place Recognition via Fast and Slow Adaptive Biasing in Event Cameras. CoRR abs/2403.16425 ( 2024) 2023.

  3. Michael Milford received the B.E. degree in mechanical and space engineering and the Ph.D. degree in electrical engineering from the University of Queensland, Brisbane, in 2002 and 2006, respectively.

  4. About. October 12, 2013 Author: Michael. Download My CV. I conduct interdisciplinary research at the boundary between robotics, neuroscience and computer vision and am a multi-award winning educational entrepreneur. My research models the neural mechanisms in the brain underlying tasks like navigation and perception to develop new technologies ...

  5. Reference publication. Please reference the following publication in any research papers: Ben Talbot, Sourav Garg, Michael Milford, “OpenSeqSLAM2.0: An Open Source Toolbox for Visual Place Recognition Under Changing Conditions,” in IEEE/RSJ International Conference on Intelligent Robots, 2018.

  6. The original RatSLAM algorithm was designed and implemented on Pioneer robots by Michael Milford and Gordon Wyeth (see RatSLAM: a hippocampal model for simultaneous localization and mapping). There is an openRatSLAM paper available in Autonomous Robots. This paper describes how openRatSLAM works in technical detail.

  7. Michael Milford. I conduct interdisciplinary research at the boundary between robotics, neuroscience and computer vision and am a multi-award winning educational entrepreneur. My research models ...

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