CNN based feature extraction and classification for sign language

• Published in: Multimedia tools and applications Vol. 80; no. 2; pp. 3051 - 3069
• Main Authors: Barbhuiya, Abul Abbas, Karsh, Ram Kumar, Jain, Rahul
• Format: Journal Article
• Language: English
• Published: New York Springer US 01.01.2021; Springer Nature B.V
• Subjects: Accuracy; Artificial neural networks; Character recognition; Classification; Computer Communication Networks; Computer Science; Data Structures and Information Theory; Error correction; Feature extraction; Feature recognition; Gesture recognition; Human-computer interaction; Human-computer interface; Literature reviews; Machine learning; Multimedia Information Systems; Sign language; Special Purpose and Application-Based Systems; Support vector machines; System effectiveness; CNN; Human–computer interface (HCI); Hand gesture; American sign language (ASL)

Hand gesture is one of the most prominent ways of communication since the beginning of the human era. Hand gesture recognition extends human-computer interaction (HCI) more convenient and flexible. Therefore, it is important to identify each character correctly for calm and error-free HCI. Literatur...