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GoogLeNet

Documentation Status standard-readme compliant Conventional Commits Commitizen friendly

GoogLeNet算法实现

GoogLeNet是基于Inception架构的CNN模型,通过在同一层中并行操作多个卷积网络,能够有效提高卷积表达能力,实现很好的分类性能。其前后实现了多个版本:

  1. GoogLeNet
  2. GoogLeNet_BN
  3. Inception_v2
  4. Inception_v3
  5. Inception_v4
  6. Inception_ResNet_v1
  7. Inception_ResNet_v2

内容列表

  • 背景
  • 安装
  • 用法
  • 主要维护人员
  • 致谢
  • 参与贡献方式
  • 许可证

背景

  • Going deeper with convolutions
  • Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift
  • Rethinking the Inception Architecture for Computer Vision
  • Inception-v4, Inception-ResNet and the Impact of Residual Connections on Learning

安装

文档工具依赖

# 文档工具依赖
$ pip install -r requirements.txt

python库依赖

$ cd py
$ pip install -r requirements.txt

用法

文档浏览

有两种使用方式

  1. 在线浏览文档:GoogLeNet

  2. 本地浏览文档,实现如下:

    $ git clone https://github.com/zjZSTU/GoogLeNet.git
    $ cd GoogLeNet
    $ mkdocs serve
    

    启动本地服务器后即可登录浏览器localhost:8000

主要维护人员

  • zhujian - Initial work - zjZSTU

致谢

引用

@misc{szegedy2014going,
    title={Going Deeper with Convolutions},
    author={Christian Szegedy and Wei Liu and Yangqing Jia and Pierre Sermanet and Scott Reed and Dragomir Anguelov and Dumitru Erhan and Vincent Vanhoucke and Andrew Rabinovich},
    year={2014},
    eprint={1409.4842},
    archivePrefix={arXiv},
    primaryClass={cs.CV}
}

@misc{ioffe2015batch,
    title={Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift},
    author={Sergey Ioffe and Christian Szegedy},
    year={2015},
    eprint={1502.03167},
    archivePrefix={arXiv},
    primaryClass={cs.LG}
}

@misc{szegedy2015rethinking,
    title={Rethinking the Inception Architecture for Computer Vision},
    author={Christian Szegedy and Vincent Vanhoucke and Sergey Ioffe and Jonathon Shlens and Zbigniew Wojna},
    year={2015},
    eprint={1512.00567},
    archivePrefix={arXiv},
    primaryClass={cs.CV}
}

@misc{szegedy2016inceptionv4,
    title={Inception-v4, Inception-ResNet and the Impact of Residual Connections on Learning},
    author={Christian Szegedy and Sergey Ioffe and Vincent Vanhoucke and Alex Alemi},
    year={2016},
    eprint={1602.07261},
    archivePrefix={arXiv},
    primaryClass={cs.CV}
}

@misc{pascal-voc-2007,
	author = "Everingham, M. and Van~Gool, L. and Williams, C. K. I. and Winn, J. and Zisserman, A.",
	title = "The {PASCAL} {V}isual {O}bject {C}lasses {C}hallenge 2007 {(VOC2007)} {R}esults",
	howpublished = "http://www.pascal-network.org/challenges/VOC/voc2007/workshop/index.html"}

@misc{pascal-voc-2012,
	author = "Everingham, M. and Van~Gool, L. and Williams, C. K. I. and Winn, J. and Zisserman, A.",
	title = "The {PASCAL} {V}isual {O}bject {C}lasses {C}hallenge 2012 {(VOC2012)} {R}esults",
	howpublished = "http://www.pascal-network.org/challenges/VOC/voc2012/workshop/index.html"}

参与贡献方式

欢迎任何人的参与!打开issue或提交合并请求。

注意:

  • GIT提交,请遵守Conventional Commits规范
  • 语义版本化,请遵守Semantic Versioning 2.0.0规范
  • README编写,请遵守standard-readme规范

许可证

Apache License 2.0 © 2020 zjZSTU

About

Implementation of GoogLeNet series Algorithm

Topics

batch-normalizationgooglenetgooglenet-bninceptioninception-resnet-v1inception-resnet-v2inception-v2inception-v3inception-v4pascal-voc-2007pascal-voc-2012pytorchresidual-learningresidual-network

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