[HTML][HTML] 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 …
[HTML][HTML] Investigating feature selection techniques to enhance the performance of EEG-based motor imagery tasks classification
Analyzing electroencephalography (EEG) signals with machine learning approaches has
become an attractive research domain for linking the brain to the outside world to establish …
become an attractive research domain for linking the brain to the outside world to establish …
[HTML][HTML] 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 …
[HTML][HTML] 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 …
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 …
Movie oriented positive negative emotion classification from eeg signal using wavelet transformation and machine learning approaches
Electroencephalography (EEG) sensor plays an important role in developing brain-computer
interfaces (BCI) to enhance human-computer interaction (HCI). Nowadays, various types of …
interfaces (BCI) to enhance human-computer interaction (HCI). Nowadays, various types of …
Skeleton-based hand gesture recognition using geometric features and spatio-temporal deep learning approach
Dynamic hand gesture recognition using a 3D skeleton dataset has become the most
attractive research domain because of the multipurpose application. Although many …
attractive research domain because of the multipurpose application. Although many …
Dynamic Hand Gesture Recognition Using Effective Feature Extraction and Attention Based Deep Neural Network.
Skeleton-based dynamic hand gesture recognition has become the most attractive and
popular research domain due to its wide range of applications. Sign language recognition …
popular research domain due to its wide range of applications. Sign language recognition …
Multi-stream graph-based deep neural networks for skeleton-based sign language recognition
Abstract Sign Language Recognition (SLR) aims to bridge speech-impaired and general
communities by recognizing signs from given videos. Researchers still face challenges …
communities by recognizing signs from given videos. Researchers still face challenges …
Motor Imagery Classification Using Effective Channel Selection of Multichannel EEG
Electroencephalography (EEG) is effectively employed to describe cognitive patterns
corresponding to different tasks of motor functions for brain–computer interface (BCI) …
corresponding to different tasks of motor functions for brain–computer interface (BCI) …