轻量化卷积神经网络实现
| CNN Architecture | Data Type (bit) | Model Size (MB) | GFlops （1080Ti） | Top-1 Acc(VOC 07+12) | Top-5 Acc(VOC 07+12) |
|---|---|---|---|---|---|
| AlexNet | 32 | 233.081 | 1.429 | 68.24% | 94.22% |
| SqueezeNet | 32 | 4.793 | 1.692 | 75.46% | 96.78% |
| SqueezeNetBypass | 32 | 4.793 | 1.692 | 77.54% | 97.41% |
- SqueezeNet: AlexNet-level accuracy with 50x fewer parameters and <0.5MB model size
- MobileNets: Efficient Convolutional Neural Networks for Mobile Vision Applications
- MobileNetV2: Inverted Residuals and Linear Bottlenecks
- ShuffleNet: An Extremely Efficient Convolutional Neural Network for Mobile
- ShuffleNet V2: Practical Guidelines for Efficient CNN Architecture Design
$ pip install -r requirements.txt
$ cd py
$ pip install -r requirements.txt
有两种使用方式
-
在线浏览文档：LightWeightCNN
-
本地浏览文档，实现如下：
$ git clone https://github.com/zjZSTU/LightWeightCNN.git $ cd LightWeightCNN $ mkdocs serve启动本地服务器后即可登录浏览器
localhost:8000
- zhujian - Initial work - zjZSTU
@misc{i2016squeezenet,
title={SqueezeNet: AlexNet-level accuracy with 50x fewer parameters and <0.5MB model size},
author={Forrest N. Iandola and Song Han and Matthew W. Moskewicz and Khalid Ashraf and William J. Dally and Kurt Keutzer},
year={2016},
eprint={1602.07360},
archivePrefix={arXiv},
primaryClass={cs.CV}
}
@misc{howard2017mobilenets,
title={MobileNets: Efficient Convolutional Neural Networks for Mobile Vision Applications},
author={Andrew G. Howard and Menglong Zhu and Bo Chen and Dmitry Kalenichenko and Weijun Wang and Tobias Weyand and Marco Andreetto and Hartwig Adam},
year={2017},
eprint={1704.04861},
archivePrefix={arXiv},
primaryClass={cs.CV}
}
@misc{s2018mobilenetv2,
title={MobileNetV2: Inverted Residuals and Linear Bottlenecks},
author={Mark Sandler and Andrew Howard and Menglong Zhu and Andrey Zhmoginov and Liang-Chieh Chen},
year={2018},
eprint={1801.04381},
archivePrefix={arXiv},
primaryClass={cs.CV}
}
@misc{zhang2017shufflenet,
title={ShuffleNet: An Extremely Efficient Convolutional Neural Network for Mobile Devices},
author={Xiangyu Zhang and Xinyu Zhou and Mengxiao Lin and Jian Sun},
year={2017},
eprint={1707.01083},
archivePrefix={arXiv},
primaryClass={cs.CV}
}
@misc{ma2018shufflenet,
title={ShuffleNet V2: Practical Guidelines for Efficient CNN Architecture Design},
author={Ningning Ma and Xiangyu Zhang and Hai-Tao Zheng and Jian Sun},
year={2018},
eprint={1807.11164},
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"}
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
Apache License 2.0 © 2020 zjZSTU