Live Demonstration: Low-Power Static Neural Network Circuits for Long-Term Change Detection

Low power neural network hardware and its new applications have been explored to exploit its inherent advantage of artificial intelligence in comparison with humans. One such application, long-term change detection, is proposed and presented in this live demonstration. Owing to the low power operati...

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Bibliographic Details
Main Authors: Marukame, Takao, Kitamura, Toshimitsu, Sugino, Junichi, Ishikawa, Kazuo, Takahashi, Koji, Tamura, Yutaka, Nishi, Yoshifumi
Format: Conference Proceeding
Language:English
Subjects:
Artificial neural networks
Biological neural networks
Deep learning
Field programmable gate arrays
Monitoring
Neurons
Online Access:Request full text
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Summary:Low power neural network hardware and its new applications have been explored to exploit its inherent advantage of artificial intelligence in comparison with humans. One such application, long-term change detection, is proposed and presented in this live demonstration. Owing to the low power operation in static analog/digital-mixed neural network circuits, our system using them can detect a change of human-friendly information, e.g., handwritten digits, whereas humans have difficulty noticing a gradual change over the long-term.
ISSN:2158-1525
DOI:10.1109/ISCAS.2019.8702246