Sign language is commonly used by deaf or speech impaired people to communicate but
requires significant effort to master. Sign Language Recognition (SLR) aims to bridge the …

Sign language recognition is a challenging problem where signs are identified by
simultaneous local and global articulations of multiple sources, ie hand shape and …

Sign language recognition (SLR) enables the deaf and speech-impaired community to
integrate and communicate effectively with the rest of society. Word level or isolated SLR is a …

Sign language recognition using computational models is a challenging problem that
requires simultaneous spatio-temporal modeling of the multiple sources, ie faces, hands …

Sign language recognition (SLR) aims to bridge speech-impaired and general communities
by recognizing signs from given videos. However, due to the complex background, light …

Abstract The performances of Sign Language Recognition (SLR) systems have improved
considerably in recent years. However, several open challenges still need to be solved to …

Sign language is commonly used by deaf or mute people to communicate but requires
extensive effort to master. It is usually performed with the fast yet delicate movement of hand …

Word-level sign language recognition (SLR) is a significant task which transcribes a sign
language video into a word. Currently, deep-learning-based frameworks mostly combine …

To extract decisive features from gesture images and solve the problem of information
redundancy in the existing gesture recognition methods, we propose a new multi-scale …

To improve computer-based recognition from video of isolated signs from American Sign
Language (ASL), we propose a new skeleton-based method that involves explicit detection …