Compact Deep Neural Networks for Computationally Efficient Gesture Classification From Electromyography Signals

Hartwell, A., Kadirkamanathan, V. and Anderson, S.R. (2018) Compact Deep Neural Networks for Computationally Efficient Gesture Classification From Electromyography Signals. 2018 7th IEEE International Conference on Biomedical Robotics and Biomechatronics (Biorob). ISSN 2155-1782

Abstract

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Authors/Creators:
  • Hartwell, A.
  • Kadirkamanathan, V.
  • Anderson, S.R.
Copyright, Publisher and Additional Information: © 2018 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other users, including reprinting/ republishing this material for advertising or promotional purposes, creating new collective works for resale or redistribution to servers or lists, or reuse of any copyrighted components of this work in other works. Reproduced in accordance with the publisher's self-archiving policy.
Keywords: Computer Vision and Pattern Recognition
Dates:
  • Accepted: 31 May 2018
  • Published: 11 October 2018
Institution: The University of Sheffield
Academic Units: The University of Sheffield > Faculty of Engineering (Sheffield) > Department of Automatic Control and Systems Engineering (Sheffield)
Depositing User: Symplectic Sheffield
Date Deposited: 13 Jul 2018 14:57
Last Modified: 24 Oct 2018 09:25
Published Version: https://doi.org/10.1109/BIOROB.2018.8487853
Status: Published
Publisher: IEEE
Refereed: Yes
Identification Number: https://doi.org/10.1109/BIOROB.2018.8487853
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