July 2018
Intermediate to advanced
310 pages
8h 21m
Chinese
Content preview from 深度学习入门 : 基于Python的理论与实现
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第 8章 深度学习
258
图8-22 Neural Image Caption（NIC）的整体结构（引用自文献[38]）
RNN的 R表示 Recurrent（递归的）。这个递归指的是神经网络的递归
的网络结构。根据这个递归结构，神经网络会受到之前生成的信息
的影响（换句话说，会记忆过去的信息），这是RNN的特征。比如，
生成“我”这个词之后，下一个要生成的词受到“我”这个词的影响，
生成了“要”；然后，再受到前面生成的“我要”的影响，生成了“睡觉”
这个词。对于自然语言、时间序列数据等连续性的数据，RNN以记
忆过去的信息的方式运行。
8.5
深度学习的未来
深度学习已经不再局限于以往的领域，开始逐渐应用于各个领域。本节
将介绍几个揭示了深度学习的可能性和未来的研究。
8.5.1
图像风格变换
有一项研究是使用深度学习来 “绘制”带有艺术气息的画。如图 8
-
23 所示，
输入两个图像后，会生成一个新的图像。两个输入图像中，一个称为“内容
图像”，另一个称为“风格图像”。
如图8
-
23 所示，如果指定将梵高的绘画风格应用于内容图像，深度学习
就会按照指示绘制出新的画作。此项研究出自论文“
A Neural Algorithm of
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