論文筆記-IGCV3：Interleaved Low-Rank Group Convolutions for Efficient Deep Neural Networks
介紹 在這篇論文中，做者同時使用低秩核和稀疏核（low-rank and sparse kernel）來組成一個密集kernel。基於ICGV2的基礎上，做者提出了ICGV3。web 近幾年，卷積網絡在計算機視覺上的有效性已經獲得了驗證。目前卷積網絡的發展主要有兩個方向：一是朝着更深的方向發展，在網絡各層之間增長skip connection，使得訓練更深的網絡成爲可能；二是簡化卷積網絡的結構，消
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相關文章
- 1. 論文筆記-IGCV3：Interleaved Low-Rank Group Convolutions for Efficient Deep Neural Networks
- 2. 【論文閱讀筆記】ECA-Net: Efficient Channel Attention for Deep Convolutional Neural Networks
- 3. 論文閱讀筆記：MobileNets: Efficient Convolutional Neural Networks for Mobile Vision Applications
- 4. 【論文閱讀筆記】MobileNets Efficient Convolutional Neural Networks for Mobile Vision Applications
- 5. MobileNets: Efficient Convolutional Neural Networks for Mobile Vision Applications論文筆記
- 6. MobileNet_v1：Efficient Convolutional Neural Networks for Mobile Vision Applications (論文筆記)
- 7. 【Learning both Weights and Connections for Efficient Neural Networks】論文筆記
- 8. 論文筆記——Aggregated Residual Transformations for Deep Neural Networks(ResNeXt)
- 9. 論文筆記——MobileNets(Efficient Convolutional Neural Networks for Mobile Vision Applications)
- 10. 論文閱讀——ECA-Net: Efficient Channel Attention for Deep Convolutional Neural Networks