Machine Learning Models Applied in Sign Language Recognition-Reference-Cited by-同舟云学术

Machine Learning Models Applied in Sign Language Recognition

Published:2023 Issue: Volume: Page:263-272
ISSN:0302-9743
Container-title:Lecture Notes in Computer Science
language:
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Author:

Novillo Quinde Esteban Gustavo^ORCID,Saldaña Torres Juan Pablo^ORCID,Alvarez Valdez Michael Andres^ORCID,Llivicota León John Santiago^ORCID,Hurtado Ortiz Remigio Ismael^ORCID

Publisher

Springer Nature Switzerland

Link

https://link.springer.com/content/pdf/10.1007/978-3-031-33783-3_25

Reference10 articles.

1. Núñez-Marcos, Adrián, Olatz Perez-de-Viñaspre, and Gorka Labaka. “A survey on Sign Language machine translation”. Expert Systems with Applications (2022): 118993

2. Obi, Y., Claudio, K.S., Budiman, V.M., Achmad, S., Kurniawan, A.: Sign language recognition system for communicating to people with disabilities. Procedia Comput. Sci. 216, 13–20 (2023). https://doi.org/10.1016/j.procs.2022.12.106

3. Saquib, N., Rahman, A.: Application of machine learning techniques for real-time sign language detection using wearable sensors. In: Proceedings of the 11th ACM Multimedia Systems Conference (2020)

4. Prognostics and Health Management of Electronics : Fundamentals, Machine Learning, and the Internet of Things, edited by Michael G. Pecht, and Myeongsu Kang, John Wiley & Sons, Incorporated, 2018. ProQuest Ebook Central

5. Raul, R.: Neural Networks : A Systematic Introduction, Springer, Berlin / Heidelberg (1996). ProQuest Ebook Central

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