Extended Hopfield Network for Sequence Learning: Application to Gesture Recognition

In this paper, we extend the Hopfield Associative Memory for storing multiple sequences of varying duration. We apply the model for learning, recognizing and encoding a set of human gestures. We measure systematically the performance of the model against noise.


Published in:
Proceedings of ICANN'05
Presented at:
ICANN'2005, 2005-09-05 00:00:00.00
Year:
2005
Other identifiers:
DAR: 7397
Laboratories:




 Record created 2005-11-16, last modified 2018-03-17

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