Abstract Automated Sign Language Recognition (SLR) aims to bridge the communication
gap between the hearing and the hearing disabled. Computer vision and deep learning lie …

Conversing with hearing disabled people is a significant challenge; however, computer
vision advancements have significantly improved this through automated sign language …

Sign language is used by deaf to communicate with other humans. It consists of not only
hand signs or gestures but encompasses also facial expressions and further body …

As a key technology to help bridging the gap between deaf and hearing people, sign
language recognition (SLR) has become one of the most active research topics in the …

Sign language is a vital tool of communication for individuals who are deaf or hard of
hearing. Sign language recognition (SLR) technology can assist in bridging the …

Sign Language Recognition (SLR) systems are crucial bridges facilitating communication
between deaf or hard-of-hearing individuals and the hearing world. Existing SLR …

Isolated Sign Language Recognition (SLR) has mostly been applied on relatively large
datasets containing signs executed slowly and clearly by a limited group of signers. In real …

Sign Language Recognition (SLR) has become an appealing topic in modern societies
because such technology can ideally be used to bridge the gap between deaf and hearing …

In this paper, a sparse coding based framework is proposed for sign language recognition
(SLR), especially for the signer-independent case. To deal with the inter-signer variation, a …

Sign language recognition (SLR) is an interesting but difficult problem. One of the biggest
challenges comes from the complex inter-signer variations. To address this problem, the …