Machine Learning for Microcontroller-Class Hardware - A Review

The advancements in machine learning opened a new opportunity to bring intelligence to the low-end Internet-of-Things nodes such as microcontrollers. Conventional machine learning deployment has high memory and compute footprint hindering their direct deployment on ultra resource-constrained microco...

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Veröffentlicht in:	IEEE sensors journal Jg. 22; H. 22; S. 1
Hauptverfasser:	Saha, Swapnil Sayan, Sandha, Sandeep Singh, Srivastava, Mani
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	United States IEEE 15.11.2022 The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Schlagworte:	Computational modeling Data models Feature projection Hardware Internet of Things Machine learning Mathematical models Microcontrollers model compression neural architecture search neural networks optimization Random access memory Sensors TinyML Workflow model compression sensors optimization neural networks Feature projection internet-of-things machine learning TinyML neural architecture search microcontrollers
ISSN:	1530-437X, 1558-1748
Online-Zugang:	Volltext
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