Sequentially Supervised Long Short-Term Memory for Gesture Recognition-Reference-Cited by-同舟云学术

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Sequentially Supervised Long Short-Term Memory for Gesture Recognition

Published:2016-03-10 Issue:5 Volume:8 Page:982-991
ISSN:1866-9956
Container-title:Cognitive Computation
language:en
Short-container-title:Cogn Comput

Author:

Wang Peisong,Song Qiang,Han Hua,Cheng Jian

Funder

Project of Chinese Academy of Sciences

National Natural Science Foundation of China

Publisher

Springer Science and Business Media LLC

Subject

Cognitive Neuroscience,Computer Science Applications,Computer Vision and Pattern Recognition

Link

http://link.springer.com/content/pdf/10.1007/s12559-016-9388-6.pdf

Reference38 articles.

1. Rautaray SS, Agrawal A. Adaptive hand gesture recognition system for multiple applications. In: Agrawal A, Tripathi RC, Yi-Luen Do E, Tiwari MD, editors. Intelligent interactive technologies and multimedia. Berlin: Springer; 2013. p. 53–65.

2. Squartini S, Schuller B, Hussain A. Cognitive and emotional information processing for human–machine interaction. Cogn Comput. 2012;4(4):383–5.

3. Xu D, Wu X, Chen YL, Xu Y. Online dynamic gesture recognition for human–robot interaction. J Intell Robot Syst. 2014;77(3–4):583–96.

4. Kröger BJ, Birkholz P, Kannampuzha J, Kaufmann E, Mittelberg I. Movements and holds in fluent sentence production of American sign language: the action-based approach. Cogn Comput. 2011;3(3):449–65.

5. Rautaray SS, Agrawal A. Vision based hand gesture recognition for human–computer interaction: a survey. Artif Intell Rev. 2015;43(1):1–54.

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