Automatic sign language recognition is a challenging task in machine learning and
computer vision. Most works have focused on recognizing sign language using hand …

Sign Language Recognition (SLR) targets on interpreting the sign language into text or
speech, so as to facilitate the communication between deaf-mute people and ordinary …

Sign language recognition (SLR) is a very challenging task due to the complexity of learning
or developing descriptors to represent its primary parameters (location, movement, and …

The communication between a person from the impaired community with a person who does
not understand sign language could be a tedious task. Sign language is the art of conveying …

Pose-based approaches for sign language recognition provide light-weight and fast models
that can be adopted in real-time applications. This article presents a framework for isolated …

Sign Language Recognition (SLR) is an essential yet challenging task since sign language
is performed with the fast and complex movement of hand gestures, body posture, and even …

Sign language, as a different form of the communication language, is important to large
groups of people in society. There are different signs in each sign language with variability …

Automatic sign language recognition is a research area that encompasses human-computer
interaction, computer vision and machine learning. Robust automatic recognition of sign …

The target of this research is to experiment, iterate and recommend a system that is
successful in recognition of American Sign Language (ASL). It is a challenging as well as an …

The paper presents the first dataset that aims to serve interdisciplinary purposes for the utility
of computer vision community and sign language linguistics. To date, a majority of Sign …