2020-12-18 20:04:54 +08:00
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# ShuffleNet: An Extremely Efficient Convolutional Neural Network for Mobile Devices
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## Introduction
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```latex
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@inproceedings{zhang2018shufflenet,
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title={Shufflenet: An extremely efficient convolutional neural network for mobile devices},
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author={Zhang, Xiangyu and Zhou, Xinyu and Lin, Mengxiao and Sun, Jian},
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booktitle={Proceedings of the IEEE conference on computer vision and pattern recognition},
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pages={6848--6856},
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year={2018}
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}
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```
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## Results and models
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### ImageNet
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| Model | Params(M) | Flops(G) | Top-1 (%) | Top-5 (%) | Config | Download |
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|:---------------------:|:---------:|:--------:|:---------:|:---------:|:---------:|:--------:|
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2020-12-21 15:29:12 +08:00
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| ShuffleNetV1 1.0x (group=3) | 1.87 | 0.146 | 68.13 | 87.81 | [config](https://github.com/open-mmlab/mmclassification/blob/master/configs/shufflenet_v1/shufflenet_v1_1x_b64x16_linearlr_bn_nowd_imagenet.py) | [model](https://download.openmmlab.com/mmclassification/v0/shufflenet_v1/shufflenet_v1_batch1024_imagenet_20200804-5d6cec73.pth) | [log](https://download.openmmlab.com/mmclassification/v0/shufflenet_v1/shufflenet_v1_batch1024_imagenet_20200804-5d6cec73.log.json) |
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