People with hearing impairments are found worldwide; therefore, the development of
effective local level sign language recognition (SLR) tools is essential. We conducted a …

Abstract 3D object recognition and pattern recognition are active and fast-growing research
areas in the field of computer vision. It is mandatory to define the pattern class, feature …

手语识别涉及计算机视觉, 模式识别, 人机交互等领域, 具有重要的研究意义与应用价值.
深度学习技术的蓬勃发展为更加精准, 实时的手语识别带来了新的机遇. 该文综述了近年来基于 …

Convolutional neural networks (CNN) have provided great advances for the task of sign
language recognition (SLR). However, recurrent neural networks (RNN) in the form of long …

At present, there are about 70 million deaf people using sign language in the world, but for
most normal people, it is difficult to understand the meaning of the sign language …

The main challenge of continuous sign language translation (CSLT) lies in the extraction of
both discriminative spatial features and temporal features. In this paper, a spatial-temporal …

Aiming the problem that the spatial-temporal hierarchical continuous sign language
recognition (CSLR) model with video as input is computationally intensive, thus limiting the …

The goal of continuous sign language recognition (CSLR) research is to apply CSLR
models as a communication tool in real life, and the real-time requirement of the models is …

Sign language recognition systems are developed to facilitate communication between
signers and non-signers. Recent field of research is intended to focus on effectively …

Sign language recognition involves computer vision, pattern recognition, human-computer
interaction, etc. It has important research significance and application value. The flourishing …