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A biologically inspired approach to learning spatio-temporal patterns.

, , , and . ICDL-EPIROB, page 291-297. IEEE, (2015)

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A biologically inspired approach to learning spatio-temporal patterns., , , and . ICDL-EPIROB, page 291-297. IEEE, (2015)Models of Intention for Human-Robot Interaction.. University of Nevada, Reno, USA, (2018)base-search.net (ftunivnevadair:oai:scholarworks.unr.edu:11714/3105).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)Grammar-based robot control., , and . AAMAS (2), page 1153-1154. IFAAMAS, (2009)A Visual Tracking Framework for Intent Recognition in Videos., , , , , and . ISVC (1), volume 5358 of Lecture Notes in Computer Science, page 450-459. Springer, (2008)A Scale and Translation Invariant Approach for Early Classification of Spatio-Temporal Patterns Using Spiking Neural Networks., , , , and . Neural Processing Letters, 43 (2): 327-343 (2016)Scale and translation invariant learning of spatio-temporal patterns using longest common subsequences and spiking neural networks., , , and . IJCNN, page 1-7. IEEE, (2015)Understanding human intentions via hidden markov models in autonomous mobile robots., , , , , and . HRI, page 367-374. ACM, (2008)Microservice-based architecture for the NRDC., , , , , , and . INDIN, page 1659-1664. IEEE, (2015)