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Generative Adversarial Network (GAN), deemed as a powerful deep-learning-based silver bullet for intelligent data generation, has been widely used in multi-disciplines. Furthermore, conditional GAN (CGAN) introduces artificial control information on the basis of GAN, which is more practical for many specific fields, though it is mostly used in domain transfer. Researchers have proposed numerous methods to tackle diverse tasks by employing CGAN. It is now a timely and also critical point to review these achievements. We first give a brief introduction to the principle of CGAN, then focus on how to improve it to achieve better performance and how to evaluate such performance across the variants. Afterward, the main applications of CGAN in domain transfer are presented. Finally, as another major contribution, we also list the current problems and challenges of CGAN.
The most well-known line of inquiry in the growing anti-deepfake research sector involves systems that can recognize artifacts or other supposedly distinguishing characteristics of deepfaked, synthesized, or otherwise falsified or 'edited' faces in video and image content. Such approaches use a v
Global wealth technology provider launches predictive planner for Microsoft Cloud for Financial Services SINGAPORE, Sept. 21, 2022 /PRNewswire/ Bambu, a global wealth technology provider, today announced the launch of their Wealth Management Predictive Planning solution for Microsoft Cloud for Financial Services and Microsoft Dynamics 365 Sales. The service will enable Relationship Managers (RMs), Financial Advisors, Agents and firms.