DeepRebirth: Accelerating Deep Neural Network Execution on Mobile Devices
DeepRebirth: Accelerating Deep Neural Network Execution on Mobile Devices 作者将CNN中的层分为两种:(1)Tensor Layer，如conv，fc；（2）Non-tensor Layer，如pooling，norm。作者发现网络进行前向推理时，Non-tensor layer也会占用不少时间和内存，作者提出用单独的Ten
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相关文章
- 1. ShuffleNet: An Extremely Efficient Convolutional Neural Network for Mobile Devices
- 2. Channel Pruning for Accelerating Very Deep Neural Networks
- 3. ISCA'18 Prediction based execution on Deep Neural Networks
- 4. Accelerating the Super-Resolution Convolutional Neural Network
- 5. 00039- AI Benchmark: Running Deep Neural Networks on Android Smartphones
- 6. Reading Note: ShuffleNet: An Extremely Efficient Convolutional Neural Network for Mobile Devices
- 7. Deep Neural Network
- 8. Deep Convolutional Neural Network Architecture
- 9. CNN 图像加强--DSLR-Quality Photos on Mobile Devices with Deep Convolutional Networks
- 10. Mobile-Efficient Convolutional Neural Network for Mobile Vision Applications