Publication Type : Book
Publisher : Springer Nature Singapore
Source : IoT Based Control Networks and Intelligent Systems: Proceedings of 3rd ICICNIS 2022 Pages 171-189, 2022
Url : https://link.springer.com/chapter/10.1007/978-981-19-5845-8_13
School : School of Engineering
Department : Electronics and Communication
Year : 2022
Abstract : Deep Generative Models are widely used to generate data that look similar to training data. Synthesis and sampling of data using Deep Generative Models can be useful for certain situations where generating data by hand would be expensive or time consuming. Data-sets for Indian Sign Language often are of small size, which hinders training of Deep Learning models to a good accuracy. In this project we attempt to compare various state-of-the-art Conditional Generative Models for Indian Sign Language Recognition task and evaluate them using various performance metrics.
Cite this Research Publication : Charan, M.G.K.S. et al. (2023). Comparative Study of Conditional Generative Models for ISL Generation. In: Joby, P.P., Balas, V.E., Palanisamy, R. (eds) IoT Based Control Networks and Intelligent Systems. Lecture Notes in Networks and Systems, vol 528. Springer, Singapore.