The Machine-Learning-Empowered Gesture Recognition Glove-Reference-Cited by-同舟云学术

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The Machine-Learning-Empowered Gesture Recognition Glove

Published:2023-02-21 Issue: Volume: Page:
ISSN:
Container-title:E-Textiles 2022
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Author:

Luo Jun¹,Qian Yuze¹,Gao Zhenyu²,Zhang Lei²,Zhuang Qinliang¹,Zhang Kun¹

Affiliation:

1. Key Laboratory of Textile Science & Technology (Ministry of Education), College of Textiles, Donghua University, Shanghai 201620, China

2. Engineering Research Center of Digitized Textile & Fashion Technology (Ministry of Education), College of Information Science & Technology, Donghua University, Shanghai 201620, China

Publisher

MDPI

Link

https://www.mdpi.com/2673-4591/30/1/19/pdf

Reference16 articles.

1. Galván-Ruiz, J., Travieso-González, C.M., Tejera-Fettmilch, A., Pinan-Roescher, A., Esteban-Hernández, L., and Domínguez-Quintana, L. (2020). Perspective and Evolution of Gesture Recognition for Sign Language: A Review. Sensors, 20.

2. Attention-based sign language recognition network utilizing keyframe sampling and skeletal features;Pan;IEEE Access,2020

3. An analysis of convolutional long short-term memory recurrent neural networks for gesture recognition;Tsironi;Neurocomputing,2017

4. Recognition of arm-and-hand visual signals by means of SVM to increase aircraft security;Saggio;Stud. Comput. Intell.,2017

5. Xue, Q., Li, X., Wang, D., and Zhang, W. (2019). Deep forest-based monocular visual sign language recognition. Appl. Sci., 9.

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