2018-17Dynamic Network Surgery for Efficient DNNs
NIPS 2016 http://arxiv.org/abs/1608.04493 code: https://github.com/yiwenguo/Dynamic-Network-Surgery 本文提出一种动态压缩CNN网络模型算法。针对 LeNet-5 和 AlexNet 可以分别减少 108倍和 17.7倍的参数，而且不损失精度。 本文主要参考了文献【9】，文献【9】通过删除一些不重要的
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相关文章
- 1. 【Dynamic Network Surgery for Efficient DNNs】论文笔记
- 2. 神经网络压缩（2）： Dynamic Network Surgery for Efficient DNNs
- 3. Optimizing Downloads for Efficient Network Access
- 4. Path-Level Network Transformation for Efficient Architecture Search
- 5. ShuffleNet: An Extremely Efficient Convolutional Neural Network for Mobile Devices
- 6. Mobile-Efficient Convolutional Neural Network for Mobile Vision Applications
- 7. 【Mimic】《Mimicking Very Efficient Network for Object Detection》
- 8. Once for All: Train One Network and Specialize it for Efficient Deployment
- 9. 论文解读：Once-for-All: Train One Network and Specialize it for Efficient Deployment
- 10. Computer assisted surgery