LeapASL: A platform for design and implementation of real time algorithms for translation of American Sign Language using personal supervised machine learning models-Reference-Cited by-同舟云学术

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LeapASL: A platform for design and implementation of real time algorithms for translation of American Sign Language using personal supervised machine learning models

Published:2022-05 Issue: Volume:12 Page:100302
ISSN:2665-9638
Container-title:Software Impacts
language:en
Short-container-title:Software Impacts

Author:

Jenkins Jon,Rashad Sherif^ORCID

Publisher

Elsevier BV

Reference12 articles.

1. Mobile sign language translation system for deaf community;Boulares,2012

2. American sign language recognition with the kinect;Zufrulla,2011

3. DeepASL: Enabling ubiquitous and non-intrusive word and sentence-level sign language translation;Fang,2018

4. American sign language recognition using hidden Markov modelsand wearable motion sensors;Fatmi;Trans. Mach. Learn. Data Min.,2017

5. Comparing ann, SVM, and HMM based machine learning methods for American sign language recognition using wearable motion sensors;Fatmi,2019

Cited by 3 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Sign language detection using convolutional neural network;Journal of Ambient Intelligence and Humanized Computing;2024-03-26

2. Machine translation from signed to spoken languages: state of the art and challenges;Universal Access in the Information Society;2023-04-01

3. A survey on Sign Language machine translation;Expert Systems with Applications;2023-03

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