Among the various fields where deep learning is used, there are challenges to be solved in
motion recognition. One is that it is difficult to manage because of the vast amount of data …

This paper presents a method of classifying sign language motion using the feature
elements extracted by using pre-trained networks. Good results for the image recognition …

Most of the existing dynamic sign language recognition methods based on deep learning
directly use the video sequence or the whole sequence based on RGB information, not just …

Continuous sign language recognition (CSLR) is an intricate task aimed at transcribing sign
language sequences from continuous video streams into sentences. Typically, deep …

Sign language recognition systems are used for enabling communication between deaf-
mute people and normal user. Spatial localization of the hands could be a challenging task …

This paper presents the results of a feasibility study of a deep learning scheme for sign
language motion recognition. Capturing the motions used in sign language was conducted …

Sign language recognition technology can help people with hearing impairments to
communicate with non-hearing-impaired people. At present, with the rapid development of …

In the past decades the set of human tasks that are solved by machines was extended
dramatically. From simple image classification problems researchers now move towards …

A new multi-sensor fusion framework is proposed, which is based on the Convolutional
Neural Network (CNN) and the Dynamic Bayesian Network (DBN) for Sign Language …

Dynamic Sign Language Recognition aims to recognize hand gestures of any person.
Dynamic Sign Language Recognition systems have challenges in recognizing the semantic …