A study on a low power optimization algorithm for an edge-AI device-Reference-Cited by-同舟云学术

A study on a low power optimization algorithm for an edge-AI device

Published:2019 Issue:4 Volume:10 Page:373-389
ISSN:2185-4106
Container-title:Nonlinear Theory and Its Applications, IEICE
language:en
Short-container-title:NOLTA

Author:

Kaneko Tatsuya¹,Orimo Kentaro¹,Hida Itaru¹,Takamaeda-Yamazaki Shinya¹,Ikebe Masayuki¹,Motomura Masato¹,Asai Tetsuya¹

Affiliation:

1. Division of Electronics for Informatics, Graduate School of Information Science and Technology (IST), Hokkaido University

Publisher

Institute of Electronics, Information and Communications Engineers (IEICE)

Subject

Rehabilitation,Physical Therapy, Sports Therapy and Rehabilitation,General Medicine

Link

https://www.jstage.jst.go.jp/article/nolta/10/4/10_373/_pdf

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4. [4] J.-Y. Zhu, T. Park, P. Isola, and A.A. Efros, “Unpaired image-to-image translation using cycle-consistent adversarial networks,” arXiv preprent, arXiv:1703.10593, 2017.

5. [5] A. van den Oord, Y. Li, I. Babuschkin, K. Simonyan, O. Vinyals, K. Kavukcuoglu, G. van den Driessche, E. Lockhart, L.C. Cobo, F. Stimberg, N. Casagrande, D. Grewe, S. Noury, S. Dieleman, E. Elsen, N. Kalchbrenner, H. Zen, A. Graves, H. King, T. Walters, D. Belov, and D. Hassabis, “Parallel WaveNet: Fast high-fidelity speech synthesis,” arXiv preprent, arXiv:1711.10433, 2017.

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