Sign Languages are expressed through hand and upper body gestures as well as facial
expressions. Therefore, Sign Language Recognition (SLR) needs to focus on all such cues …

Sign language plays a crucial role as a distinct and vital mode of communication for diverse
groups of people in society. Each sign language encompasses a wide array of signs, each …

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 …

Independent Sign Language Recognition is a complex visual recognition problem that
combines several challenging tasks of Computer Vision due to the necessity to exploit and …

The large majority of sign language recognition systems based on deep learning adopt a
word model approach. Here we present a system that works with subunits, rather than word …

Hand gesture serves as a critical role in sign language. Current deep-learning-based sign
language recognition (SLR) methods may suffer insufficient interpretability and overfitting …

This paper proposes an attentional network for the task of Continuous Sign Language
Recognition. The proposed approach exploits co-independent streams of data to model the …

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 …

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 …

Abstract Gestures in American Sign Language (ASL) are characterized by fast, highly
articulate motion of upper body, including arm movements with complex hand shapes and …