Results 1 to 10 of about 5,743,277 (287)

Real-time sign language recognition based on YOLO algorithm

Neural computing & applications (Print)
This study focuses on real-time hand gesture recognition in the Turkish sign language detection system. YOLOv4-CSP based on convolutional neural network (CNN), a state-of-the-art object detection algorithm, is used to provide real-time and high ...
Melek Alaftekin, I. Paçal, Kenan Cicek
semanticscholar   +1 more source

An integrated mediapipe-optimized GRU model for Indian sign language recognition

Scientific Reports, 2022
Sign language recognition is challenged by problems, such as accurate tracking of hand gestures, occlusion of hands, and high computational cost. Recently, it has benefited from advancements in deep learning techniques.
Barathi Subramanian, Bekhzod Olimov, Shraddha M. Naik, Sang-Chul Kim, Kil-Houm Park, Jeonghong Kim   +5 more
semanticscholar   +1 more source

Review on Deep Learning-Based Dynamic Indian Sign Language Recognition System

ITEGAM-JETIA
An alternative form of communication for those who are hard of hearing or speech is sign language (SL). SL differs from nation to nation. Indian Sign Language (ISL) is a substitute form of communication used by individuals in India.
Manojkumar Patel, Narendra Patel
doaj   +1 more source

Dynamic Sign Language Recognition Based on Video Sequence With BLSTM-3D Residual Networks

IEEE Access, 2019
Sign language recognition aims to recognize meaningful movements of hand gestures and is a significant solution in intelligent communication between the deaf community and hearing societies.
Yanqiu Liao, Pengwen Xiong, Weidong Min, Weiqiong Min, Jiahao Lu   +4 more
doaj   +1 more source

Advancements in Sign Language Recognition: A Comprehensive Review and Future Prospects

IEEE Access
Sign language (SL) is a vital mode of communication, bridging the gap between the hearing impaired and hearing communities. However, SL, despite its paramount importance, has received relatively limited attention from researchers.
Bashaer A. Al Abdullah, Ghada A. Amoudi, H. Alghamdi   +2 more
semanticscholar   +1 more source

A Study on the STGCN-LSTM Sign Language Recognition Model Based on Phonological Features of Sign Language

IEEE Access
Many isolated words in Chinese Sign Language (CSL) exhibit significant feature similarities, which are primarily conveyed through hand, face, and body movements.
Yuxin Han, Yong Han, Qi Jiang
doaj   +1 more source

Tanzanian sign language recognition system for an assistive communication glove sign tutor based on the inertial sensor fusion control algorithm

Journal of Electrical Systems and Information Technology
This paper presents a sign language recognition system for sign tutoring assistive hand data gloves for hearing-impaired people. In this study, specially designed 5-fingered data gloves are used for interaction and communication with hearing-impaired or ...
Isack Bulugu
doaj   +1 more source

An Adam based CNN and LSTM approach for sign language recognition in real time for deaf people

Bulletin of Electrical Engineering and Informatics
Hand gestures and sign language are crucial modes of communication for deaf individuals. Since most people can't understand sign language, it's hard for a mute and an average person to talk to each other.
Subrata Kumer Paul, Md. Abul Ala Walid, Rakhi Rani Paul, M. Uddin, Md. Sohel Rana, Maloy Kumar Devnath, Ishaat Rahman Dipu, M. Haque   +7 more
semanticscholar   +1 more source

Sign Language Recognition Based on CNN-BiLSTM Using RF Signals

IEEE Access
As the number of individuals with speech and hearing impairments continues to grow, the demand for sign language recognition systems is increasing. Furthermore, most radio frequency-based gesture recognition systems have primarily focused on simple ...
Yajun Zhang, Yuankang Wang, Feng Li, Weiqian Yu, Congcong Wang, Ying Jiang   +5 more
doaj   +1 more source

Video-based automatic sign language recognition

工程科学与技术, 2011
:In video-based automatic gesture recognition, interfering factors such as hand occlusion and color closeness between background and skin of the signer often result in errors in hand segmentation and hand tracking.
Zhang Sheng-Jun
doaj