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ArASL: Arabic Alphabets Sign Language Dataset
A fully-labelled dataset of Arabic Sign Language (ArSL) images is developed for research related to sign language recognition. The dataset will provide researcher the opportunity to investigate and develop automated systems for the deaf and hard of hearing people using machine learning, computer vis...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Elsevier
2019
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6661066/ https://www.ncbi.nlm.nih.gov/pubmed/31372425 http://dx.doi.org/10.1016/j.dib.2019.103777 |
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author | Latif, Ghazanfar Mohammad, Nazeeruddin Alghazo, Jaafar AlKhalaf, Roaa AlKhalaf, Rawan |
author_facet | Latif, Ghazanfar Mohammad, Nazeeruddin Alghazo, Jaafar AlKhalaf, Roaa AlKhalaf, Rawan |
author_sort | Latif, Ghazanfar |
collection | PubMed |
description | A fully-labelled dataset of Arabic Sign Language (ArSL) images is developed for research related to sign language recognition. The dataset will provide researcher the opportunity to investigate and develop automated systems for the deaf and hard of hearing people using machine learning, computer vision and deep learning algorithms. The contribution is a large fully-labelled dataset for Arabic Sign Language (ArSL) which is made publically available and free for all researchers. The dataset which is named ArSL2018 consists of 54,049 images for the 32 Arabic sign language sign and alphabets collected from 40 participants in different age groups. Different dimensions and different variations were present in images which can be cleared using pre-processing techniques to remove noise, center the image, etc. The dataset is made available publicly at https://data.mendeley.com/datasets/y7pckrw6z2/1. |
format | Online Article Text |
id | pubmed-6661066 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | Elsevier |
record_format | MEDLINE/PubMed |
spelling | pubmed-66610662019-08-01 ArASL: Arabic Alphabets Sign Language Dataset Latif, Ghazanfar Mohammad, Nazeeruddin Alghazo, Jaafar AlKhalaf, Roaa AlKhalaf, Rawan Data Brief Computer Science A fully-labelled dataset of Arabic Sign Language (ArSL) images is developed for research related to sign language recognition. The dataset will provide researcher the opportunity to investigate and develop automated systems for the deaf and hard of hearing people using machine learning, computer vision and deep learning algorithms. The contribution is a large fully-labelled dataset for Arabic Sign Language (ArSL) which is made publically available and free for all researchers. The dataset which is named ArSL2018 consists of 54,049 images for the 32 Arabic sign language sign and alphabets collected from 40 participants in different age groups. Different dimensions and different variations were present in images which can be cleared using pre-processing techniques to remove noise, center the image, etc. The dataset is made available publicly at https://data.mendeley.com/datasets/y7pckrw6z2/1. Elsevier 2019-02-23 /pmc/articles/PMC6661066/ /pubmed/31372425 http://dx.doi.org/10.1016/j.dib.2019.103777 Text en © 2019 The Authors http://creativecommons.org/licenses/by/4.0/ This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Computer Science Latif, Ghazanfar Mohammad, Nazeeruddin Alghazo, Jaafar AlKhalaf, Roaa AlKhalaf, Rawan ArASL: Arabic Alphabets Sign Language Dataset |
title | ArASL: Arabic Alphabets Sign Language Dataset |
title_full | ArASL: Arabic Alphabets Sign Language Dataset |
title_fullStr | ArASL: Arabic Alphabets Sign Language Dataset |
title_full_unstemmed | ArASL: Arabic Alphabets Sign Language Dataset |
title_short | ArASL: Arabic Alphabets Sign Language Dataset |
title_sort | arasl: arabic alphabets sign language dataset |
topic | Computer Science |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6661066/ https://www.ncbi.nlm.nih.gov/pubmed/31372425 http://dx.doi.org/10.1016/j.dib.2019.103777 |
work_keys_str_mv | AT latifghazanfar araslarabicalphabetssignlanguagedataset AT mohammadnazeeruddin araslarabicalphabetssignlanguagedataset AT alghazojaafar araslarabicalphabetssignlanguagedataset AT alkhalafroaa araslarabicalphabetssignlanguagedataset AT alkhalafrawan araslarabicalphabetssignlanguagedataset |