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深度学习入门 : 基于Python的理论与实现
book

深度学习入门 : 基于Python的理论与实现

by 斋藤康毅
July 2018
Intermediate to advanced
310 pages
8h 21m
Chinese
Posts & Telecom Press
Content preview from 深度学习入门 : 基于Python的理论与实现
8.5  深度学习的未来 
259
Artistic Style”
[39]
,一经发表就受到全世界的广泛关注。
这里我们不会介绍这项研究的详细内容,只是叙述一下这个技术的大致
框架,即刚才的方法是在学习过程中使网络的中间数据近似内容图像的中间
数据。这样一来,就可以使输入图像近似内容图像的形状。此外,为了从风
格图像中吸收风格,导入了风格矩阵的概念。通过在学习过程中减小风格矩
阵的偏差,就可以使输入图像接近梵高的风格。
8.5.2
 图像的生成
刚才的图像风格变换的例子在生成新的图像时输入了两个图像。不同于
这种研究,现在有一种研究是生成新的图像时不需要任何图像(虽然需要事
8-23  基于论文“A Neural Algorithm of Artistic Style”的图像风格变换的例子:左上
角是风格图像,右上角是内容图像,下面的图像是新生成的图像(图像引用自文献 [40]
8章 深度学习
260
先使用大量的图像进行学习,但在“画”新图像时不需要任何图像)。比如,
基于深度学习,可以实现从零生成“卧室”的图像。图8
-
24 中展示的图像是
基于
DCGAN
Deep Convolutional Generative Adversarial Network
[41]
法生成的卧室图像的例子。
8-24 基于 ...
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Publisher Resources

ISBN: 9787115485588