模型压缩：Networks Slimming-Learning Efficient Convolutional Networks through Network Slimming

时间 2020-07-20

标签模型压缩 networks slimming learning efficient convolutional network 栏目系统网络繁體版

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Network Slimming-Learning Efficient Convolutional Networks through Network Slimming（Paper） 2017年ICCV的一篇paper，思路清晰，骨骼清奇~~git 创新点： 1. 利用batch normalization中的缩放因子γ 做为重要性因子，即γ越小，所对应的channel不过重要，就能够裁剪（prun

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1. 模型压缩：Networks Slimming-Learning Efficient Convolutional Networks through Network Slimming
2. 模型压缩之Learning Efficient Convolutional Networks through Network Slimming
3. 模型剪枝----Learning Efficient Convolutional Networks through Network Slimming
4. 《Learning Efficient Convolutional Networks through Network Slimming》论文笔记
5. 【论文阅读笔记】Learning Efficient Convolutional Networks through Network Slimming
6. DL经典文章翻译2：Learning Efficient Convolutional Networks through Network Slimming
7. [论文理解] Learning Efficient Convolutional Networks through Network Slimming
8. 【Pruning系列：一】Learning Efficient Convolutional Networks through Network Slimming
9. 【Pruning系列：二】Learning Efficient Convolutional Networks through Network Slimming｜YOLOv3实践｜Pytorch 总结
10. 模型压缩
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1. 模型压缩：Networks Slimming-Learning Efficient Convolutional Networks through Network Slimming
2. 模型压缩之Learning Efficient Convolutional Networks through Network Slimming
3. 模型剪枝----Learning Efficient Convolutional Networks through Network Slimming
4. 《Learning Efficient Convolutional Networks through Network Slimming》论文笔记
5. 【论文阅读笔记】Learning Efficient Convolutional Networks through Network Slimming
6. DL经典文章翻译2：Learning Efficient Convolutional Networks through Network Slimming
7. [论文理解] Learning Efficient Convolutional Networks through Network Slimming
8. 【Pruning系列：一】Learning Efficient Convolutional Networks through Network Slimming
9. 【Pruning系列：二】Learning Efficient Convolutional Networks through Network Slimming｜YOLOv3实践｜Pytorch 总结
10. 模型压缩

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