Few-Shot User-Definable Radar-Based Hand Gesture Recognition at the Edge

Author:

Mauro Gianfranco1ORCID,Chmurski Mateusz1,Servadei Lorenzo1ORCID,Pegalajar-Cuellar Manuel2ORCID,Morales-Santos Diego P.2ORCID

Affiliation:

1. Infineon Technologies AG, Neubiberg, Germany

2. Department of Electronic and Computer Technology, University of Granada, Granada, Spain

Funder

ITEA3 Unleash Potentials in Simulation

German Federal Ministry of Education and Research

Austrian Research Promotion Agency

Rijksdienst voor Ondernemend Nederland

Innovation Fund Denmark

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

General Engineering,General Materials Science,General Computer Science

Reference69 articles.

1. Meta-learning: A survey;vanschoren;arXiv 1810 03548,2018

2. Facing the reality of data stream classification: coping with scarcity of labeled data

3. Learning IoT in Edge: Deep Learning for the Internet of Things with Edge Computing

4. What is the state of neural network pruning?;blalock;arXiv 2003 03033,2020

5. Distilling the knowledge in a neural network;hinton;ArXiv 1503 02531,2015

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