Vision-Based American Sign Language Classification Approach via Deep Learning
Hearing-impaired is the disability of partial or total hearing loss that causes a significant problem for communication with other people in society. American Sign Language (ASL) is one of the sign languages that most commonly used language used by Hearing impaired communities to communicate with ea...
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| Format: | Article |
| Language: | English |
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LibraryPress@UF
2022-05-01
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| Series: | Proceedings of the International Florida Artificial Intelligence Research Society Conference |
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| Online Access: | https://journals.flvc.org/FLAIRS/article/view/130616 |
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| author | Nelly Elsayed |
| author_facet | Nelly Elsayed |
| author_sort | Nelly Elsayed |
| collection | DOAJ |
| description | Hearing-impaired is the disability of partial or total hearing loss that causes a significant problem for communication with other people in society. American Sign Language (ASL) is one of the sign languages that most commonly used language used by Hearing impaired communities to communicate with each other. In this paper, we proposed a simple deep learning model that
aims to classify the American Sign Language letters as a step in a path for removing communication barriers that are related to disabilities. |
| format | Article |
| id | doaj-art-4bcd4cfc9d524d269e9e0e1dd00c17c0 |
| institution | DOAJ |
| issn | 2334-0754 2334-0762 |
| language | English |
| publishDate | 2022-05-01 |
| publisher | LibraryPress@UF |
| record_format | Article |
| series | Proceedings of the International Florida Artificial Intelligence Research Society Conference |
| spelling | doaj-art-4bcd4cfc9d524d269e9e0e1dd00c17c02025-08-20T03:05:26ZengLibraryPress@UFProceedings of the International Florida Artificial Intelligence Research Society Conference2334-07542334-07622022-05-013510.32473/flairs.v35i.13061666815Vision-Based American Sign Language Classification Approach via Deep LearningNelly Elsayed0University of CincinnatiHearing-impaired is the disability of partial or total hearing loss that causes a significant problem for communication with other people in society. American Sign Language (ASL) is one of the sign languages that most commonly used language used by Hearing impaired communities to communicate with each other. In this paper, we proposed a simple deep learning model that aims to classify the American Sign Language letters as a step in a path for removing communication barriers that are related to disabilities.https://journals.flvc.org/FLAIRS/article/view/130616american sign languagedeep learningconvolution neural networkgesture classification |
| spellingShingle | Nelly Elsayed Vision-Based American Sign Language Classification Approach via Deep Learning Proceedings of the International Florida Artificial Intelligence Research Society Conference american sign language deep learning convolution neural network gesture classification |
| title | Vision-Based American Sign Language Classification Approach via Deep Learning |
| title_full | Vision-Based American Sign Language Classification Approach via Deep Learning |
| title_fullStr | Vision-Based American Sign Language Classification Approach via Deep Learning |
| title_full_unstemmed | Vision-Based American Sign Language Classification Approach via Deep Learning |
| title_short | Vision-Based American Sign Language Classification Approach via Deep Learning |
| title_sort | vision based american sign language classification approach via deep learning |
| topic | american sign language deep learning convolution neural network gesture classification |
| url | https://journals.flvc.org/FLAIRS/article/view/130616 |
| work_keys_str_mv | AT nellyelsayed visionbasedamericansignlanguageclassificationapproachviadeeplearning |