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Journal of Robotics
Volume 2017, Article ID 2061827, 7 pages
https://doi.org/10.1155/2017/2061827
Research Article

Long Short-Term Memory Projection Recurrent Neural Network Architectures for Piano’s Continuous Note Recognition

1School of Information Science and Technology, Beijing Forestry University, No. 35 Qinghuadong Road, Haidian District, Beijing 100083, China
2National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences, No. 95 Zhongguancundong Road, Haidian District, Beijing 100190, China
3College of Information Science and Technology, Jinan University, No. 601, West Huangpu Avenue, Guangzhou, Guangdong 510632, China

Correspondence should be addressed to Yanyan Xu; nc.ude.ufjb@naynayux

Received 10 May 2017; Revised 30 July 2017; Accepted 6 August 2017; Published 12 September 2017

Academic Editor: Keigo Watanabe

Copyright © 2017 YuKang Jia et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

How to Cite this Article

YuKang Jia, Zhicheng Wu, Yanyan Xu, Dengfeng Ke, and Kaile Su, “Long Short-Term Memory Projection Recurrent Neural Network Architectures for Piano’s Continuous Note Recognition,” Journal of Robotics, vol. 2017, Article ID 2061827, 7 pages, 2017. https://doi.org/10.1155/2017/2061827.