The survey paper summarizes the recent applications and developments in the domain of Generative Adversarial Networks (GANs) i.e. a back propagation based neural network architecture for generative modeling. GANs is one of the most highlighted research avenue due to its synthetic data generation capabilities and benefits of representations comprehended irrespective of the application. While several reviews for GANs in the arena of image processing have been conducted by present but none have given attention on the review of GANs over multi-disciplinary domains. Therefore, in this survey, use of GAN in multidisciplinary applications areas and its implementation challenges have been done by conducting a rigorous search for journal/research article related to GAN and in this regard five renowned journal databases i.e. “ACM Digital Library”,” Elsevier”, “IEEE Explore”, “Science Direct”, “Springer” and proceedings of best domain specific conference are considered. By employing hybrid research methodology and article inclusion and exclusion criteria, 100 research articles are considered encompassing 23 application domains for the survey. In this paper applications of GAN in various practical domain and their implementation challenges its associated advantages and disadvantages have been discussed. For the first time a survey of this type have been done where GAN with wide range of application and its associated advantages and disadvantages issue have been reviewed. Finally, this article presents several diversified prominent developing trends in the respective research domain which will provide a visionary perspective regarding ongoing GANs related research and eventually help to develop an intuition for problem solving using GANs.

该调查论文总结了生成对抗网络（GAN）领域的最新应用和发展，即用于生成建模的基于反向传播的神经网络架构。GANs 是最突出的研究途径之一，因为它具有合成数据生成能力和不受应用程序影响的表示的好处。虽然目前已经对图像处理领域的 GAN 进行了几次审查，但没有人关注跨学科领域的 GAN 审查。因此，在本次调查中，通过严格搜索与 GAN 相关的期刊/研究文章以及在这方面的五个著名期刊数据库，即“ACM 数字图书馆”，GAN 在多学科应用领域的使用及其实施挑战已经完成。” Elsevier”、“IEEE Explore”、“Science Direct”、“Springer”和最佳领域特定会议论文集被考虑在内。通过采用混合研究方法和文章纳入和排除标准，100 篇研究文章被认为涵盖了调查的 23 个应用领域。本文讨论了 GAN 在各种实际领域中的应用及其实施挑战，讨论了其相关的优缺点。首次进行了此类调查，其中审查了具有广泛应用范围的 GAN 及其相关的优缺点问题。最后，