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A methodological and structural review of hand gesture recognition across diverse data modalities
Researchers have been develo** Hand Gesture Recognition (HGR) systems to enhance
natural, efficient, and authentic human-computer interaction, especially benefiting those who …
natural, efficient, and authentic human-computer interaction, especially benefiting those who …
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 …
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 …
Hand gesture recognition for multi-culture sign language using graph and general deep learning network
Hand gesture-based Sign Language Recognition (SLR) serves as a crucial communication
bridge between hard of hearing and non-deaf individuals. The absence of a universal sign …
bridge between hard of hearing and non-deaf individuals. The absence of a universal sign …
Multistage spatial attention-based neural network for hand gesture recognition
The definition of human-computer interaction (HCI) has changed in the current year because
people are interested in their various ergonomic devices ways. Many researchers have …
people are interested in their various ergonomic devices ways. Many researchers have …
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 …
Korean sign language alphabet recognition through the integration of handcrafted and deep learning-based two-stream feature extraction approach
Recognizing sign language plays a crucial role in improving communication accessibility for
the Deaf and hard-of-hearing communities. In Korea, many individuals facing hearing and …
the Deaf and hard-of-hearing communities. In Korea, many individuals facing hearing and …
[HTML][HTML] Deep learning-based bangla sign language detection with an edge device
S Siddique, S Islam, EE Neon, T Sabbir… - Intelligent Systems with …, 2023 - Elsevier
Sign language, often referred to as silent conversation, serves as a visual gesture-based
primary communication medium for hearing-impaired individuals. People unable to speak or …
primary communication medium for hearing-impaired individuals. People unable to speak or …