Patil, "Time-frequency masking-based speech enhancement using generative adversarial network," in Proc. International Conf. on Acoustic, Speech and Signal Processing, 2018. [19] S. Fu, C. Liao, Y. Tsao and S. Lin, "Metricgan: Generative adversarial networks based black-box metric scores ...
intra预测的过程被表述为一个基于学习的inpainting task,利用GAN的generator在已经解码的block的基础上对缺失的部分进行预测,充分利用邻域信息,可以更好的预测当前待编码单元。 使用提出的GAN方法对intra预测模块进行了重新设计,并进行了率失真操作(RDO),以在传统方法和GAN方法之间选择最佳方法,并附加一个标记。 在编码器...
membership inference generative adversarial networks based leakage attacks against collaborative deep learning Introduction 通过探测模型的输出和辅助统计人口信息推断病人的基因组信息,使用预测置信度(分类)回顾训练数据(人脸) private data用于生成模型训练 生成模型生成数据用于下游任务 可用性的前提:保存数据整体特征 有...
Generative adversarial networks (GANs) are becoming increasingly important in the artificial construction of realistic images and related functionalities1,2,3,4,5,6,7,8. GANs are based on two types of networks called generators and discriminators, which are denoted byGandD, respectively, in Fig.1...
However, the RUL methods based on deep learning demand sufficient and varied samples of critical components from run to failure. To compensate for the lack of samples, generative adversarial networks (GAN) and conditional generative adversarial networks (CGAN) are proposed [20–22]. Although GAN an...
we present a novel image-based path planning algorithm to overcome these limitations. Specifically, a generative adversarial network (GAN) is designed to take the environment map (denoted as RGB image) as the input without other preprocessing works. The output is also an RGB image where the prom...
Most of the prior methods based on this technology involve computer vision applications. However, we improve the existing network structure of a generative adversarial network by adding the encoder network and a signal spatial transform module, allowing our framework to address radio signal processing ...
Here, we propose a generative machine learning model (MatGAN) based on a generative adversarial network (GAN) for efficient generation of new hypothetical inorganic materials. Trained with materials from the ICSD database, our GAN model can generate hypothetical materials not existing in the training...
You might not think that programmers are artists, but programming is an extremely creative profession. It’s logic-based creativity. - John Romero 在你眼里,程序员也许未必是艺术家,但是,编程是一种基于逻辑且极具创造性的职业, 1. 什么是生成对抗网络(Generative Adversarial Network, GAN)?
摘要:生成式对抗网络(Generative adversarial networks, GAN)是当前人工智能学界最为重要的研究热点之一。其突出的生成能力不仅可用于生成各类图像和自然语言数据,还启发和推动了各类半监督学习和无监督学习任务的发展。 本文概括了GAN的基本思想,并对近年来相关的理论与应用研究进行了梳理,总结了GAN常见的网络结构与训练...