关于生成式对抗神经网络研究的思路探析

On the thinking of research on GAN network

通过对生成式对抗神经网络(Generative Adversarial Networks,简称GAN)进行探析,介绍了深度学习的发展和应用以及GAN的基本思想和应用领域。接着阐述GAN的基础理论,包括生成模型和判别模型、GAN的基本原理和数学模型以及GAN的训练方法和算法。然后介绍GAN的改进算法和技术以及在图像生成、视频生成、文本生成等领域的应用,并讨论了GAN的实用性和可靠性评估。最后探讨GAN的发展趋势和挑战,包括未来的发展方向和趋势、技术挑战和解决方案以及社会和伦理问题。

By exploring Generative Adversarial Networks(GAN),the article introduces the development and application of deep learning as well as the basic ideas and application areas of GAN.Then the basic theory of GAN is elaborated,including generative mod⁃el and discriminative model,the basic principle and mathematical model of GAN,and the training method and algorithm of GAN.Then it introduces the improved algorithms and techniques of GAN and its applications in the fields of image generation,video generation,text generation,etc.,and discusses the practicality and reliability assessment of GAN.Finally,the trends and challenges of GAN are discussed,including future directions and trends,technical challenges and solutions,and social and ethical issues.