Image Based HTM Word Recognizer for Language processing [Article]
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Date
2019-11-29
Authors
James, Alex Pappachen
Irmanova, Aidana
Krestinskaya, Olga
Journal Title
Journal ISSN
Volume Title
Publisher
Institute of Electrical and Electronics Engineers
Abstract
The hardware implementation of neuro-inspired machine learning algorithms for near sensor processing on edge devices is an open problem. In this work, we propose a solution to written word recognition problem related to sequence learning tasks with images. Applying a theoretical framework of neocortex functionality as a sequence learning algorithm on a hardware implementation of Hierarchical Temporal Memory (HTM), we test the potential use of HTM in near-sensor on-chip natural language processing for text/symbol recognition.
Description
https://ieeexplore.ieee.org/document/8552117
Keywords
HTM Word Recognizer, Language Processing, Hierarchical Temporal Memory, Research Subject Categories::TECHNOLOGY
Citation
Irmanova, A., Krestinskaya, O., & James, A. P. (2018). Image Based HTM Word Recognizer for Language Processing. In 2018 IEEE International Conference on Consumer Electronics - Asia (ICCE-Asia). IEEE. https://doi.org/10.1109/icce-asia.2018.8552117