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.
Original language | English (US) |
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Title of host publication | 2018 IEEE International Conference on Consumer Electronics - Asia, ICCE-Asia 2018 |
Publisher | Institute of Electrical and Electronics Engineers Inc. |
ISBN (Print) | 9781538658079 |
DOIs | |
State | Published - Nov 28 2018 |
Externally published | Yes |