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Thomas Collins

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This is just a disambiguation page, and is not intended to be the bibliography of an actual person. Any publication listed on this page has not been assigned to an actual author yet. If you know the true author of one of the publications listed below, you are welcome to contact us.

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2020 – today

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2021
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Alexandre K. Ligo, Krista Rand, Jason Bassett, Stephanie Elisabeth Galaitsi, Benjamin D. Trump, Bamini Jayabalasingham, Thomas Collins, Igor Linkov:
Comparing the Emergence of Technical and Social Sciences Research in Artificial Intelligence. Frontiers Comput. Sci. 3: 653235 (2021)

2010 – 2019

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2016
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Anthony Spears, Michael E. West, Matthew Meister, Jacob Buffo, Catherine Walker, Thomas Collins, Ayanna M. Howard, Britney E. Schmidt:
Under Ice in Antarctica: The Icefin Unmanned Underwater Vehicle Development and Deployment. IEEE Robotics Autom. Mag. 23(4): 30-41 (2016)
2014
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Anthony Spears, Thomas Collins, Michael E. West, Ayanna M. Howard:
Evaluation of sonar and video data collection efforts in an under-ice environment using an unmanned underwater vehicle. SMC 2014: 813-818
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Anthony Spears, Ayanna M. Howard, Michael E. West, Thomas Collins:
Determining underwater vehicle movement from sonar data in relatively featureless seafloor tracking missions. WACV 2014: 909-916
2011
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Thomas Collins:
Occupancy Grid Learning Using Contextual Forward Modelling. J. Intell. Robotic Syst. 64(3-4): 505-542 (2011)
2010
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Thomas Collins, John P. T. Moore:
An Inverse Sensor Model for Earthquake Detection using Mobile Devices. ICINCO (3) 2010: 81-86

2000 – 2009

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2007
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Thomas Collins, J. J. Collins, Conor Ryan:
Improved occupancy grid learning - the conform approach to occupancy grid mapping. ICINCO-RA (2) 2007: 492-497
2005
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Thomas Collins, J. J. Collins, Mark Mansfield, Shane O'Sullivan:
Evaluating Techniques for Resolving Redundant Information and Specularity in Occupancy Grids. Australian Conference on Artificial Intelligence 2005: 235-244
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Mark Mansfield, J. J. Collins, Malachy Eaton, Thomas Collins:
N-Learning: A Reinforcement Learning Paradigm for Multiagent Systems. Australian Conference on Artificial Intelligence 2005: 684-694

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