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A New Dataset and Proposed Convolutional Neural Network Architecture for Classification of American Sign Language Digits

arXiv 2011.08927 ↗First posted 16 Nov 2020cs.CV cs.CLcited by 4

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Abstract (arXiv)

According to interviews with people who work with speech impaired persons, speech impaired people have difficulties in communicating with other people around them who do not know the sign language, and this situation may cause them to isolate themselves from society and lose their sense of independence. With this paper, to increase the quality of life of individuals with facilitating communication between individuals who use sign language and who do not know this language, a new American Sign Language (ASL) digits dataset that can help to create machine learning algorithms which need to large and varied data to be successful created and published as Sign Language Digits Dataset on Kaggle Datasets web page, a proposal Convolutional Neural Network (CNN) architecture that can get 98% test accuracy on our dataset presented, and compared with the existing popular CNN models.

Key facts. Cited by 4 papers in the map (data through 7 Oct 2026). First posted on arXiv 16 Nov 2020.

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Citing papers per year: 2023: 3; 2024: 0; 2025: 0; 2026: 1.

4 papers.