摘要
大数据技术的飞速发展,促使海量数据的处理成本逐渐降低,因此在图像处理领域,建立在大量数据无监督训练基础上的生成对抗网络具有很大优势。本文围绕生成对抗网络的发展轨迹,对其本身与各类变种网络的研究进展进行追踪,进而对生成对抗网络在图像领域的原理及研究进展进行调研总结。对比分析了目前较为热门的典型生成对抗网络模型,并对其在计算机视觉领域的应用进行了分析和总结。
The rapid development of big data technology has led to a gradual reduction in the processing cost of massive data,and therefore the GAN based on unsupervised training of large amounts of data has great advantages in the field of image processing.In this paper,we trace the development of GAN and its variants,and then summarize the principles and research progress of GAN in the field of image processing.The popular typical GAN models are compared and analyzed,and their applications in the field of computer vision are analyzed and summarized.
作者
张晨曦
姚琼
秦飞巍
葛瑞泉
Zhang Chenxi;Yao Qiong;Qin Feiwei;Ge Ruiquan(School of Computer Science and Technology,Hangzhou Dianzi University,Hangzhou,Zhejiang 310018,China;Taizhou Middle School)
出处
《计算机时代》
2023年第8期11-15,共5页
Computer Era
基金
杭州电子科技大学教育教学改革研究资助项目(SGJYB202206,YBJG202137)。
关键词
生成对抗网络
图像识别
卷积神经网络
图像生成
generative adversarial network(GAN)
image recognition
convolutional neural network(CNN)
image generation
