going deeper with convolutions 参考文献"Going Deeper with Convolutions" 是一篇关于深度卷积神经网络架构的重要论文,由 Christian Szegedy 等人于 2014 年在 IEEE 发表。这篇论文首次介绍了 Inception 模块和 GoogLeNet 架构,该架构在当年的 ImageNet 大规模视觉识别挑战赛(ILSVRC)中取得了优秀的成绩。 参考文献格式...
computer vision, codenamed Inception, which derives its name from the Network in network paper by Lin et al [12] in conjunction with the famous “we need to go deeper” internet meme [1]. In our case, the word “deep” is used in two different meanings: first of all, in the...
论文名称:Going Deeper with Convolutions 作者:Christian Szegedy, Wei Liu & Yangqing Jia等 paper 前言 本文的组织方式是按照论文的顺序,逐段进行分析,论文重点内容加粗表示,同时在每一小节的最后进行总结,以便理清作者思路,把握论文的主要内容。因水平有限,不免有疏漏之处,如有发现,恳请指出!
class BasicConv2d(nn.Module): def __init__(self, in_channels, out_channels, **kwargs): super(BasicConv2d, self).__init__() self.conv = nn.Conv2d(in_channels, out_channels, **kwargs) self.relu = nn.ReLU(inplace=True) def forward(self, x): x = self.conv(x) x = self.re...
一、基本信息 标题:Going deeper with convolutions 时间:2014 出版源:IEEE 论文领域:深度学习,CNN 引用格式:Szegedy C, Liu W, Jia Y, et al. Going deeper with convolutions[C]//Proceedings of the IEEE conference on computer vision an...
Going Deeper with Convolutions 论文下载 https://volctracer.com/w/BX18q92F 论文作者 Christian Szegedy, Wei Liu, Yangqing Jia, Pierre Sermanet, Scott Reed, Dragomir Anguelov, Dumitru Erhan, Vincent Vanhoucke, Andrew Rabinovich 内容简介 这篇论文提出了一种深度卷积神经网络架构，代号为Inception（也称...
论文笔记:Going deeper with convolutions 一、基本信息 标题:Going deeper with convolutions 时间:2014 出版源:IEEE 论文领域:深度学习,CNN 引用格式:Szegedy C, Liu W, Jia Y, et al. Going deeper with convolutions[C]//Proceedings of the IEEE conference on computer vision an......
Szegedy C, Liu W, Jia Y, et al. Going deeper with convolutions[C]. computer vision and pattern recognition, 2015: 1-9. @article{szegedy2015going, titl
Going deeper with convolutions 用卷积层让网络更深 Christian Szegedy, Google Inc. 谷歌公司 Wei Liu, University of North Carolina, Chapel Hill 北卡罗来纳大学教堂山分校 Yangqing Jia, Google Inc. 谷歌公司 Pierre Sermanet, Google Inc. 谷歌公司 ...
[论文阅读]Going deeper with convolutions(GoogLeNet) 本文采用的GoogLenet网络(代号Inception)在2014年ImageNet大规模视觉识别挑战赛取得了最好的结果,该网络总共22层。 Motivation and High Level Considerations 提升深度神经网络的一个最直接的方法就是增加网络的大小。这包括增加网络的深度(网络的层数)和宽度(每一层...