2018-17Dynamic Network Surgery for Efficient DNNs
NIPS 2016 http://arxiv.org/abs/1608.04493 code: https://github.com/yiwenguo/Dynamic-Network-Surgery 本文提出一種動態壓縮CNN網絡模型算法。針對 LeNet-5 和 AlexNet 可以分別減少 108倍和 17.7倍的參數，而且不損失精度。 本文主要參考了文獻【9】，文獻【9】通過刪除一些不重要的
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相關文章
- 1. 【Dynamic Network Surgery for Efficient DNNs】論文筆記
- 2. 神經網絡壓縮（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. 論文解讀：Once-for-All: Train One Network and Specialize it for Efficient Deployment
- 10. Computer assisted surgery