Comparison between handcraft feature extraction and methods based on Recurrent Neural Network models for gesture recognition by instrumented gloves: A case for Brazilian Sign Language Alphabet-Reference-Cited by-同舟云学术

Comparison between handcraft feature extraction and methods based on Recurrent Neural Network models for gesture recognition by instrumented gloves: A case for Brazilian Sign Language Alphabet

Published:2023-02 Issue: Volume:80 Page:104201
ISSN:1746-8094
Container-title:Biomedical Signal Processing and Control
language:en
Short-container-title:Biomedical Signal Processing and Control

Author:

Dias Thiago Simões^ORCID,Mendes José Jair Alves,Pichorim Sérgio Francisco

Funder

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior

Publisher

Elsevier BV

Subject

Health Informatics,Signal Processing,Biomedical Engineering

Reference27 articles.

1. Static gestures recognition for Brazilian sign language with kinect sensor;Bessa Carneiro,2016

2. A survey on sign language recognition using smartphones;Ghanem,2017

3. Sign language recognition using multiple kernel learning: A case study of Pakistan sign language;Shah;IEEE Access,2021

4. American sign language alphabet recognition by extracting feature from hand pose estimation;Shin;Sensors,2021

5. Vision-based hand gesture recognition using deep learning for the interpretation of sign language;Sharma;Expert Syst. Appl.,2021

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