TinyML: Current Progress, Research Challenges, and Future Roadmap

被引：44
|
作者：
Shafique, Muhammad [1 ]
Theocharides, Theocharis [2 ]
Reddy, Vijay Janapa [3 ]
Murmann, Boris [4 ]
机构：
[1] New York Univ Abu Dhabi, Abu Dhabi, U Arab Emirates
[2] Univ Cyprus, Nicosia, Cyprus
[3] Harvard Univ, Cambridge, MA 02138 USA
[4] Stanford Univ, Stanford, CA 94305 USA
来源：
2021 58TH ACM/IEEE DESIGN AUTOMATION CONFERENCE (DAC) | 2021年
关键词：
TinyML; Machine Learning; Deep Learning; Benchmarking; Edge-Al;
D O I：
10.1109/DAC18074.2021.9586232
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
TinyML: tiny in size, BIG in impact! This paper highlights the current progress, challenges and open research opportunities in the domain of tinyML, benchmarking, and emerging applications for Edge-AI.
引用
收藏
页码：1303 / 1306
页数：4
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