Human–machine interaction in intelligent and connected vehicles: A review of status quo, issues, and opportunities
Z Tan, N Dai, Y Su, R Zhang, Y Li… - IEEE Transactions on …, 2021 - ieeexplore.ieee.org
Human–Machine Interaction (HMI) in Intelligent and Connected Vehicles (ICVs) has drawn
great attention in recent years due to its potentially significant positive impacts on the …
great attention in recent years due to its potentially significant positive impacts on the …
Dynamic hand gesture recognition using multi-branch attention based graph and general deep learning model
The dynamic hand skeleton data have become increasingly attractive to widely studied for
the recognition of hand gestures that contain 3D coordinates of hand joints. Many …
the recognition of hand gestures that contain 3D coordinates of hand joints. Many …
Korean sign language recognition using transformer-based deep neural network
Sign language recognition (SLR) is one of the crucial applications of the hand gesture
recognition and computer vision research domain. There are many researchers who have …
recognition and computer vision research domain. There are many researchers who have …
Multi-stream general and graph-based deep neural networks for skeleton-based sign language recognition
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 …
by recognizing signs from given videos. However, due to the complex background, light …
[PDF][PDF] Rotation, Translation and Scale Invariant Sign Word Recognition Using Deep Learning.
Communication between people with disabilities and people who do not understand sign
language is a growing social need and can be a tedious task. One of the main functions of …
language is a growing social need and can be a tedious task. One of the main functions of …
Dynamic fall detection using graph-based spatial temporal convolution and attention network
The prevention of falls has become crucial in the modern healthcare domain and in society
for improving ageing and supporting the daily activities of older people. Falling is mainly …
for improving ageing and supporting the daily activities of older people. Falling is mainly …
Sign language recognition using graph and general deep neural network based on large scale dataset
Sign Language Recognition (SLR) represents a revolutionary technology aiming to
establish communication between hearing impaired and non-hearing impaired …
establish communication between hearing impaired and non-hearing impaired …
Dynamic Korean sign language recognition using pose estimation based and attention-based neural network
Sign language recognition is crucial for improving communication accessibility for the
hearing impaired community and reducing dependence on human interpreters. Notably …
hearing impaired community and reducing dependence on human interpreters. Notably …
A Deep Bidirectional LSTM Model Enhanced by Transfer-Learning-Based Feature Extraction for Dynamic Human Activity Recognition
Dynamic human activity recognition (HAR) is a domain of study that is currently receiving
considerable attention within the fields of computer vision and pattern recognition. The …
considerable attention within the fields of computer vision and pattern recognition. The …
Sign Language Recognition: A Comprehensive Review of Traditional and Deep Learning Approaches, Datasets, and Challenges
T Tao, Y Zhao, T Liu, J Zhu - IEEE Access, 2024 - ieeexplore.ieee.org
The Deaf are a large social group in society. Their unique way of communicating through
sign language is often confined within their community due to limited understanding by …
sign language is often confined within their community due to limited understanding by …