Sign Language Recognition by Means of Common Spatial Patterns-Reference-Cited by-同舟云学术

Sign Language Recognition by Means of Common Spatial Patterns

Published:2021-01-29 Issue: Volume: Page:
ISSN:
Container-title:2021 The 5th International Conference on Machine Learning and Soft Computing
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Author:

Rodríguez-Moreno Itsaso¹,Martínez-Otzeta José María¹,Goienetxea Izaro¹,Sierra Basilio¹

Affiliation:

1. University of the Basque Country(UPV/EHU), Spain

Funder

The Spanish Ministry of Science (MCIU), the State Research Agency (AEI) and the European Regional Development Fund (FEDER)

Basque Government, Spain

Spanish Ministry of Science, Innovation and Universities

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/3453800.3453818

Reference13 articles.

1. Zhe Cao Gines Hidalgo Tomas Simon Shih-En Wei and Yaser Sheikh. 2018. OpenPose: realtime multi-person 2D pose estimation using Part Affinity Fields. arXiv preprint arXiv:1812.08008(2018). Zhe Cao Gines Hidalgo Tomas Simon Shih-En Wei and Yaser Sheikh. 2018. OpenPose: realtime multi-person 2D pose estimation using Part Affinity Fields. arXiv preprint arXiv:1812.08008(2018).

2. Automatic sign language recognition: A survey

3. Application of the Karhunen-Loève Expansion to Feature Selection and Ordering

4. Sign language recognition with recurrent neural network using human keypoint detection

5. Camillo Lugaresi Jiuqiang Tang Hadon Nash Chris McClanahan Esha Uboweja Michael Hays Fan Zhang Chuo-Ling Chang Ming Guang Yong Juhyun Lee 2019. MediaPipe: A framework for building perception pipelines. arXiv preprint arXiv:1906.08172(2019). Camillo Lugaresi Jiuqiang Tang Hadon Nash Chris McClanahan Esha Uboweja Michael Hays Fan Zhang Chuo-Ling Chang Ming Guang Yong Juhyun Lee 2019. MediaPipe: A framework for building perception pipelines. arXiv preprint arXiv:1906.08172(2019).

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