arXiv Open Access 2022

Vision-Based American Sign Language Classification Approach via Deep Learning

Nelly Elsayed Zag ElSayed Anthony S. Maida

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Abstrak

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.

Topik & Kata Kunci

cs.CV cs.LG

Penulis (3)

Nelly Elsayed

Zag ElSayed

Anthony S. Maida

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APA MLA BibTeX

Elsayed, N., ElSayed, Z., Maida, A.S. (2022). Vision-Based American Sign Language Classification Approach via Deep Learning. https://arxiv.org/abs/2204.04235

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Informasi Jurnal

Tahun Terbit: 2022
Bahasa: en
Sumber Database: arXiv
Akses: Open Access ✓