Sequence recognition with spatio-temporal long-term memory organization

• Main Authors: Nguyen, Vu Anh, Goh, Wooi Boon, Starzyk, Janusz A.
• Other Authors: School of Computer Engineering
• Format: Conference or Workshop Item
• Language: English
• Published: 2013
• Subjects: DRNTU::Engineering::Computer science and engineering
• Online Access: https://hdl.handle.net/10356/98284; http://hdl.handle.net/10220/12399
• Institution: Nanyang Technological University

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.