Author:
Sonawane Neel,Kulkarni Anagha,Deshmukh Pratiksha
Reference13 articles.
1. Y. Robert, Y. Nigudkar, A. Kulkarni, N. Mutha, and P. Barve, “Literature survey: Application of machine learning techniques on static sign language recognition,” in Innovations in Bio-Inspired Computing and Applications, edited by A. Abraham, H. Sasaki, R. Rios, N. Gandhi, U. Singh, and K. Ma (Springer International Publishing, Cham, 2021) pp. 179–186.
2. A. Patil, A. Kulkarni, H. Yesane, M. Sadani, and P. Satav, “Literature survey: Sign language recognition using gesture recognition and natural language processing,” in Data Management, Analytics and Innovation, edited by N. Sharma, A. Chakrabarti, V. E. Balas, and A. M. Bruckstein (Springer Singapore, Singapore, 2021) pp. 197–210.
3. P. Barve, N. Mutha, A. Kulkarni, Y. Nigudkar, and Y. Robert, “Application of deep learning techniques on sign language recognition—asurvey,” in Data Management, Analytics and Innovation, edited by N. Sharma, A. Chakrabarti, V. E. Balas, and A. M. Bruckstein (Springer Singapore, Singapore, 2021) pp. 211–227.
4. S. C. J and Lijiya, Signet: A Deep Learning based Indian Sign Language Recognition System (International Conference on Communicationand Signal Processing, 2019).
5. R. S. A. Prachi Sharma, “A comprehensive evaluation of deep models and optimizers for indian sign language recognition,graphics and visualcomputing,” (December 2021).