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ShuffleNet: An Extremely Efficient Convolutional Neural Network for Mobile Devices
時間 2020-12-29
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channel shuffle 文章對CNN進行改進,採用pointwise convolution 和 channel shuffle,保持精度的同時,減少了計算量,加快了計算速度. 在ImageNet classification and MS COCO上的實驗上取得了比top1,即mobile net,錯誤率減小6.7%.相比AlexNet,計算速度提高13倍,同時精度基本不變. CNN網絡
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相關文章
1.
ShuffleNet: An Extremely Efficient Convolutional Neural Network for Mobile Devices
2.
【論文閱讀筆記】ShuffleNet: An Extremely Efficient Convolutional Neural Network for Mobile Devices
3.
論文閱讀筆記:ShuffleNet: An Extremely Efficient Convolutional Neural Network for Mobile Devices
4.
【論文閱讀】ShuffleNet: An Extremely Efficient Convolutional Neural Network for Mobile Devices
5.
Paper Reading: ShuffleNet: An Extremely Efficient Convolutional Neural Network for Mobile Devices
6.
ShuffleNet: An Extremely Efficient Convolutional Neural Network for Mobile Devices的理解
7.
ShuffleNet: An Extremely Efficient Convolutional Neural Network for Mobile Devices閱讀
8.
論文筆記:ShuffleNet: An Extremely Efficient Convolutional Neural Network for Mobile Devices
9.
【論文學習記錄】ShuffleNet: An Extremely Efficient Convolutional Neural Network for Mobile Devices
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Reading Note: ShuffleNet: An Extremely Efficient Convolutional Neural Network for Mobile Devices
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