SML: A Skeleton-based multi-feature learning method for sign language recognition-Reference-Cited by-同舟云学术

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SML: A Skeleton-based multi-feature learning method for sign language recognition

Published:2024-10 Issue: Volume:301 Page:112288
ISSN:0950-7051
Container-title:Knowledge-Based Systems
language:en
Short-container-title:Knowledge-Based Systems

Author:

Deng Zhiwen,Leng Yuquan,Hu Jing,Lin Zengrong,Li Xuerui,Gao Qing^ORCID

Publisher

Elsevier BV

Reference71 articles.

1. SKIM: Skeleton-based isolated sign language recognition with part mixing;Lin;IEEE Trans. Multimed.,2024

2. Robust real-time hand detection and localization for space human–robot interaction based on deep learning;Gao;Neurocomputing,2020

3. A comparative study of evaluating and benchmarking sign language recognition system-based wearable sensory devices using a single fuzzy set;Qahtan;Knowl.-Based Syst.,2023

4. StepNet: Spatial-temporal part-aware network for isolated sign language recognition;Shen;ACM Trans. Multimedia Comput. Commun. Appl.,2024

5. Sign language recognition using 3d convolutional neural networks;Huang,2015

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