Learning to Clean: A GAN Perspective

Author:

Sharma Monika,Verma Abhishek,Vig Lovekesh

Publisher

Springer International Publishing

Reference26 articles.

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2. Chen, X., Duan, Y., Houthooft, R., Schulman, J., Sutskever, I., Abbeel, P.: InfoGAN: Interpretable representation learning by information maximizing generative adversarial nets. CoRR abs/1606.03657 (2016). http://arxiv.org/abs/1606.03657

3. Farahmand, A., Sarrafzadeh, A., Shanbehzadeh, J.: Document image noises and removal methods. In: Proceedings of the International MultiConference of Engineers and Computer Scientists 2013, vol. 1 (2013). http://www.iaeng.org/publication/IMECS2013/IMECS2013_pp436-440.pdf

4. Frank, A.: UCI machine learning repository. University of California, School of information and computer science, Irvine, CA (2010). http://archive.ics.uci.edu/ml

5. Ganbold, G.: History document image background noise and removal methods. Int. J. Knowl. Content Dev. Technol. 5, 11 (2015). http://ijkcdt.net/xml/05531/05531.pdf

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