Comparative Study of Optimization Algorithm in Deep CNN-Based Model for Sign Language Recognition-Reference-Cited by-同舟云学术

Comparative Study of Optimization Algorithm in Deep CNN-Based Model for Sign Language Recognition

Published:2021-09-14 Issue: Volume: Page:463-471
ISSN:2367-4512
Container-title:Computer Networks and Inventive Communication Technologies
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Author:

Rajan Rajesh George,Rajendran P. Selvi

Publisher

Springer Singapore

Link

https://link.springer.com/content/pdf/10.1007/978-981-16-3728-5_35

Reference15 articles.

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2. Hinton, G.E., Salakhutdinov, R.R.: Reducing the dimensionality of data with neural networks. Science 313(5786), 504–507 (2006)

3. Hinton, G., Deng, L., Yu, D., Dahl, G.E., Mohamed, A.-R., Jaitly, N., Senior, A., Vanhoucke, V., Nguyen, P., Sainath, T.N., et al.: Deep neural networks for acoustic modeling in speech recognition: The shared views of four research groups. Signal Process. Mag. IEEE 29(6), 82–97 (2012)

4. Graves, A., Mohamed, A.-R., Hinton, G.: Speech recognition with deep recurrent neural networks. In: 2013 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), pp. 6645–6649. IEEE (2013)

5. Duchi, J., Hazan, E., Singer, Y.: Adaptive subgradient methods for online learning and stochastic optimization. J. Mach. Learn. Res. 12, 2121–2159 (2011)

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