Bioformers: Embedding Transformers for Ultra-Low Power sEMG-based Gesture Recognition-Reference-Cited by-同舟云学术

Bioformers: Embedding Transformers for Ultra-Low Power sEMG-based Gesture Recognition

Published:2022-03-14 Issue: Volume: Page:
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Container-title:2022 Design, Automation & Test in Europe Conference & Exhibition (DATE)
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Author:

Burrello Alessio¹,Morghet Francesco Bianco²,Scherer Moritz³,Benatti Simone⁴,Benini Luca¹,Macii Enrico⁵,Poncino Massimo²,Pagliari Daniele Jahier²

Affiliation:

1. DEI, Universitá di Bologna,Bologna,Italy

2. Politecnico di Torino,Department of Control and Computer Engineering,Turin,Italy

3. ETH Zurich,Integrated Systems Laboratory,Switzerland

4. University of Modena and Reggio Emilia,Department of Sciences and Methods for Engineering,Italy

5. Politecnico di Torino,Interuniversity Department of Regional and Urban Studies and Planning,Turin,Italy

Publisher

IEEE

Link

Reference26 articles.

1. Bert: Pre-training of deep bidirectional transformers for language understanding;devlin;ArXiv Preprint,2018

2. Language models are few-shot learners;brown;ArXiv Preprint,2020

3. An image is worth 16×16 words: Transformers for image recognition at scale;dosovitskiy;ArXiv Preprint,2020

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