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 7章 卷积神经网络
232
综上，
LeNet
与现在的
CNN
虽然有些许不同，但差别并不是那么大。
想到
LeNet
是20 多年前提出的最早的
CNN
，还是很令人称奇的。
7.7.2
AlexNet
在
LeNet
问世20 多年后，
AlexNet
被发布出来。
AlexNet
是引发深度学
习热潮的导火线，不过它的网络结构和
LeNet
基本上没有什么不同，如图 7
-
28
所示。
图7-28 AlexNet（根据文献[21] 生 成）
22
4
11
11
55
27
13
13
13
13
13
13
27
256
384 384 256
4096 4096
1000
55
5
3
5
3
3
3
3
3
96
max
pooling
fully
connected
max
pooling
224
3
AlexNet
叠有多个卷积层和池化层，最后经由全连接层输出结果。虽然
结构上
AlexNet
和
LeNet
没有大的不同，但有以下几点差异。
•
激活函数使用 ReLU。
•
使用进行局部正规化的 LRN（Local Response Normalization）层 。
•
使用 Dropout（6.4.3节 ）。
如上所述，关于网络结构，
LeNet
和
AlexNet
没有太大的不同。但是，
围绕它们的环境和计算机技术有了很大的进步。具体地说，现在任何人都可
以获得大量的数据。而且，擅长大规模并行计算的
GPU
得到普及，高速进
行大量的运算已经成为可能。大数据和
GPU
已成为深度学习发展的巨大的
原动力。
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