《NetAdapt：Platform-Aware Neural Network Adaptation for Mobile Applications》論文筆記
代碼地址：netadapt 1. 概述 導讀：這篇文章提出了一個新的網絡壓縮算法NetAdapt，它使用一個預訓練好的模型在固定計算資源的手機平臺上進行壓縮試驗，因而可以直接採集壓縮之後的直接性能表現（計算耗時與功耗）作爲feedback，文章指出其爲direct metrics。像連乘累加操作（MACs）和網絡權重數量這些常規的間接測量方式並不能很好反應網絡的性能，這是因爲它們與計算耗時和功耗並
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相關文章
- 1. Mobile-Efficient Convolutional Neural Network for Mobile Vision Applications
- 2. 每天一篇論文 319/365 NetAdapt: Platform-Aware Neural Network Adaptation for Mobile Applications
- 3. （MobileNets）Efficient Convolutional Neural Networks for Mobile Vision Applications論文閱讀筆記
- 4. MobileNets: Efficient Convolutional Neural Networks for Mobile Vision Applications論文筆記
- 5. 論文閱讀筆記：MobileNets: Efficient Convolutional Neural Networks for Mobile Vision Applications
- 6. MobileNet_v1：Efficient Convolutional Neural Networks for Mobile Vision Applications (論文筆記)
- 7. 論文筆記：MobileNets: Efficient Convolutional Neural Networks for Mobile Vision Applications Andrew
- 8. 【論文閱讀筆記】MobileNets Efficient Convolutional Neural Networks for Mobile Vision Applications
- 9. 論文筆記 MobileNets:Efficient Convolutional Neural Networks for Mobile Vision Applications
- 10. 論文筆記——MobileNets(Efficient Convolutional Neural Networks for Mobile Vision Applications)