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Update 第四章_经典网络.md

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@ -236,8 +236,9 @@ GoogLeNet作为2014年ILSVRC在分类任务上的冠军，以6.65%的错误率
​ 如图4.9中所示，GoogLeNet相比于以前的卷积神经网络结构，除了在深度上进行了延伸，还对网络的宽度进行了扩展，整个网络由许多块状子网络的堆叠而成，这个子网络构成了Inception结构。图4.9为Inception的四个版本：$Inception_{v1}$在同一层中采用不同的卷积核，并对卷积结果进行合并;$Inception_{v2}$组合不同卷积核的堆叠形式，并对卷积结果进行合并;$Inception_{v3}$则在$v_2$基础上进行深度组合的尝试;$Inception_{v4}​$结构相比于前面的版本更加复杂，子网络中嵌套着子网络。
![](./img/ch4/img_inception_02.png)
<img src="./img/ch4/img_inception_05.png" width="250" height="250" /><img src="./img/ch4/img_inception_06.png" width="240" height="250" /><img src="./img/ch4/img_inception_07.png" width="270" height="250" />
![](./img/ch4/img_inception_03.png)![](./img/ch4/img_inception_04.png)
![](./img/ch4/img_inception_05.png)
![](./img/ch4/img_inception_03.png)
![](./img/ch4/img_inception_04.png)
​ 图 4.10 Inception$_{v1-4}$结构图
​ 表 4.6 GoogLeNet中Inception$_{v1}$网络参数配置