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Unsupervised Learning of Spatio-temporal Patterns Using Spike Timing Dependent Plasticity.

, , , and . AGI, volume 8598 of Lecture Notes in Computer Science, page 254-257. Springer, (2014)

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A biologically inspired approach to learning spatio-temporal patterns., , , and . ICDL-EPIROB, page 291-297. IEEE, (2015)Context-Based Bayesian Intent Recognition., , , , , and . IEEE Trans. Auton. Ment. Dev., 4 (3): 215-225 (2012)Models of Intention for Human-Robot Interaction.. University of Nevada, Reno, USA, (2018)base-search.net (ftunivnevadair:oai:scholarworks.unr.edu:11714/3105).Deep networks for predicting human intent with respect to objects., , , , , and . HRI, page 171-172. ACM, (2012)Unsupervised Learning of Spatio-temporal Patterns Using Spike Timing Dependent Plasticity., , , and . AGI, volume 8598 of Lecture Notes in Computer Science, page 254-257. Springer, (2014)Integrating Context into Intent Recognition Systems., , , , , and . ICINCO (2), page 315-320. INSTICC Press, (2010)Liability in Robotics: An International Perspective on Robots as Animals., , , and . Adv. Robotics, 24 (13): 1861-1871 (2010)Robots as animals: A framework for liability and responsibility in human-robot interactions., , and . RO-MAN, page 72-77. IEEE, (2009)The Quiescent Intracluster Medium in the Core of the Perseus Cluster, , , , , , , , , and 206 other author(s). (2016)cite arxiv:1607.04487Comment: 31 pages, 11 Figs, published in Nature July 8.A Vision-Based Architecture for Intent Recognition., , , , , and . ISVC (2), volume 4842 of Lecture Notes in Computer Science, page 173-182. Springer, (2007)