Efficient Brazilian Sign Language Recognition: A Study on Mobile Devices-Reference-Cited by-同舟云学术

Efficient Brazilian Sign Language Recognition: A Study on Mobile Devices

Published:2023-11-27 Issue: Volume: Page:406-419
ISSN:0302-9743
Container-title:Progress in Pattern Recognition, Image Analysis, Computer Vision, and Applications
language:
Short-container-title:

Author:

Fabris Vitor Lopes^ORCID,de Castro Bastos Felype^ORCID,de Faria Ana Claudia Akemi Matsuki^ORCID,da Silva José Victor Nogueira Alves^ORCID,Luiz Pedro Augusto^ORCID,Custódio Silva Rafael^ORCID,De Paris Renata^ORCID,dos Santos Claudio Filipi Gonçalves^ORCID

Publisher

Springer Nature Switzerland

Link

https://link.springer.com/content/pdf/10.1007/978-3-031-49018-7_29

Reference31 articles.

1. Amaresh, M., Chitrakala, S.: Video captioning using deep learning: an overview of methods, datasets and metrics. In: 2019 International Conference on Communication and Signal Processing (ICCSP), pp. 0656–0661 (2019). https://doi.org/10.1109/ICCSP.2019.8698097

2. Cerna, L.R., Cardenas, E.E., Miranda, D.G., Menotti, D., Camara-Chavez, G.: A multimodal LIBRAS-UFOP Brazilian sign language dataset of minimal pairs using a microsoft kinect sensor. Expert Syst. Appl. 167, 114179 (2021)

3. Dalal, N., Triggs, B.: Histograms of oriented gradients for human detection. In: 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR 2005), pp. 886–893 (2005). https://doi.org/10.1109/CVPR.2005.177

4. de Castro, G.Z., et al: Desenvolvimento de uma base de dados de sinais de libras para aprendizado de máquina: Estudo de caso com CNN 3D. In: Anais do 14Ž Simpósio Brasileiro de Automação Inteligente (2019). https://doi.org/10.17648/sbai-2019-111451

5. de Castro, G.Z., Guerra, R.R., Guimarães, F.G.: Automatic translation of sign language with multi-stream 3D CNN and generation of artificial depth maps. Expert Syst. Appl. 215, 119394 (2023)