Please use this identifier to cite or link to this item: https://hdl.handle.net/10356/98284
Title: Sequence recognition with spatio-temporal long-term memory organization
Authors: Nguyen, Vu Anh
Goh, Wooi Boon
Starzyk, Janusz A.
Keywords: DRNTU::Engineering::Computer science and engineering
Issue Date: 2012
Source: Nguyen, V. A., Starzyk, J. A., & Goh, W. B. (2012). Sequence recognition with spatio-temporal long-term memory organization. The 2012 International Joint Conference on Neural Networks (IJCNN).
Abstract: In this work, we propose a connectionist memory structure for spatio-temporal sequence learning and recognition inspired by the Long-Term Memory structure of human cortex. Besides symbolic data, our framework is able to continuously process real-valued multi-dimensional data stream. This capability is made possible by addressing three critical problems in spatio-temporal learning, namely error tolerance, significance of sequence's elements and memory forgetting mechanism. We demonstrate the potential of the framework with a synthetic example and a real world example, namely the task of hand-sign language interpretation with the Australian Sign Language dataset.
URI: https://hdl.handle.net/10356/98284
http://hdl.handle.net/10220/12399
DOI: http://dx.doi.org/10.1109/IJCNN.2012.6252682
Rights: © 2012 IEEE.
Fulltext Permission: none
Fulltext Availability: No Fulltext
Appears in Collections:SCSE Conference Papers

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