Signer-Independent Arabic Sign Language Recognition System Using Deep Learning Model.

ABSTRACT: Every one of us has a unique manner of communicating to explore the world, and such communication helps to interpret life. Sign language is the popular language of communication for hearing and speech-disabled people. When a sign language user interacts with a non-sign language user, it becomes difficult for a signer to express themselves to another person. A sign language recognition system can help a signer to interpret the sign of a non-sign language user. This study presents a sign language recognition system that is capable of recognizing Arabic Sign Language from recorded RGB videos. To achieve this, two datasets were considered, such as (1) the raw dataset and (2) the face-hand region-based segmented dataset produced from the raw dataset. Moreover, operational layer-based multi-laye

SUBMITTER: Podder KK 

PROVIDER: S-EPMC10459624 | biostudies-literature | 2023 Aug

REPOSITORIES: biostudies-literature