Tiny Machine Learning
Tiny Machine Learning is a machine learning paradigm that enables the deployment of optimized models capable of performing inference and training directly on resource-constrained microcontroller-based edge devices within Internet of Things embedded systems, distinguished by extreme efficiency in memory, power, and computational requirements.
228
Publications
10.8K
Citations
723
Authors
254
Institutions
Publications per year
2017–2026
227
Variants
Tinyml
228
A Comprehensive Survey on TinyML
Youssef Abadade, Anas Temouden, Hatim Bamoumen et al. · IEEE Access · 2023 · 289 citations · Full text
MCUNet: Tiny Deep Learning on IoT Devices
Ji Lin, Wei-Ming Chen, Yujun Lin et al. · arXiv (Cornell University) · 2020 · 257 citations · Full text
Benchmarking TinyML Systems: Challenges and Direction
Colby Banbury, Vijay Janapa Reddi, Max W. Y. Lam et al. · arXiv (Cornell University) · 2020 · 198 citations · Full text
1–5 of 228
723
8
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7
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7
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7
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Ollscoil na Gaillimhe – University of Galway, Ireland
6 publications · 209 citations
6
h-index
1–5 of 723
254

Harvard University Press
Cambridge, United States
9 h-index
28 publications
1.3K citations

University of Bologna
Bologna, Italy
6 h-index
12 publications
677 citations
Politecnico di Milano
Milan, Italy
6 h-index
12 publications
362 citations
ETH Zurich
Zurich, Switzerland
6 h-index
10 publications
382 citations

Ollscoil na Gaillimhe – University of Galway
Galway, Ireland
5 h-index
13 publications
359 citations

University of Leeds
Leeds, United Kingdom
5 h-index
8 publications
354 citations
Dublin City University
Dublin, Ireland
5 h-index
5 publications
158 citations
Mid Sweden University
Sundsvall, Sweden
5 h-index
3 publications
129 citations
1–8 of 254
Repository · 29 publications · 1.9K citations
19
h-index
7 publications · 227 citations
12
h-index
10 publications · 484 citations
12
h-index
8 publications · 623 citations
10
h-index
Conference · 4 publications · 107 citations
5
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1–5