Hand Gesture Recognition for Multi-Culture Sign Language Using Graph and General Deep Learning Network

• Published in: IEEE open journal of the Computer Society Vol. 5; pp. 1 - 12
• Main Authors: Miah, Abu Saleh Musa, Hasan, Md. Al Mehedi, Tomioka, Yoichi, Shin, Jungpil
• Format: Journal Article
• Language: English
• Published: New York IEEE 01.01.2024; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: American Sign Language (ASL); Artificial neural networks; Bangla Sign Language (BSL); Convolutional neural networks; Cultural differences; Culture; Deep learning; Feature extraction; GCN; Gesture recognition; Graph meets with Attention and CNN (GmTC); Hand Gesture Recognition (HGR); Hidden Markov models; Japanese Sign Language (JSL); Korean sign language (KSL); Machine learning; McSL; MHSA; Modules; Sign language; SLR; Transformers

Hand gesture-based Sign Language Recognition (SLR) serves as a crucial communication bridge between deaf and non-deaf individuals. The absence of a universal sign language (SL) leads to diverse nationalities having various cultural SLs, such as Korean, American, and Japanese sign language. Existing...