Affiliation:
1. University of Louisiana at Lafayette, USA
Abstract
Generative adversarial networks have been a highly focused research topic in computer vision, especially in image synthesis and image-to-image translation. There are a lot of variations in generative nets, and different GANs are suitable for different applications. In this chapter, the authors investigated conditional generative adversarial networks to generate fake images, such as handwritten signatures. The authors demonstrated an implementation of conditional generative adversarial networks, which can generate fake handwritten signatures according to a condition vector tailored by humans.
Reference9 articles.
1. Competition, transmission and bank pricing policies: Evidence from Belgian loan and deposit markets
2. Synthetic generation of handwritten signatures based on spectral analysis;J.Galbally;Optics and Photonics in Global Homeland Security V and Biometric Technology for Human Identification VI,2009
3. Generative adversarial nets.;I.Goodfellow;Advances in Neural Information Processing Systems,2014
4. Melo. (2019). Deep learning approach to generate offline handwritten signatures based on online samples. IET Biometrics, 8(3), 215-220.