Publication Type : Book
Publisher : Springer Nature Singapore
Source : Inventive Systems and Control: Proceedings of ICISC 2022 Pages 489-502, 2022
Url : https://link.springer.com/chapter/10.1007/978-981-19-1012-8_33
Campus : Amritapuri
School : School of Engineering
Department : Electronics and Communication
Year : 2022
Abstract : There is a long drawn communication barrier between normal people and deaf-mute community. Sign language is a major tool of communication for hearing impaired people. The goal of this work is to develop a Convolutional Neural Network (CNN) based Indian sign language classifier. CNN models with combination of different hidden layers are analysed and the model giving highest accuracy is selected. Further synthetic data is generated using Conditional Generative Adversarial Network (CGAN), in order to improve classification accuracy.
Cite this Research Publication : Charan, M.G.K.S. et al. (2022). Sign Language Recognition Using CNN and CGAN. In: Suma, V., Baig, Z., Kolandapalayam Shanmugam, S., Lorenz, P. (eds) Inventive Systems and Control. Lecture Notes in Networks and Systems, vol 436. Springer, Singapore. https://doi.org/10.1007/978-981-19-1012-8_33