CondenseNet: An Efficient DenseNet Using Learned Group Convolutions

@article{Huang2018CondenseNetAE,
  title={CondenseNet: An Efficient DenseNet Using Learned Group Convolutions},
  author={Gao Huang and Shichen Liu and Laurens van der Maaten and Kilian Q. Weinberger},
  journal={2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition},
  year={2018},
  pages={2752-2761}
}
Deep neural networks are increasingly used on mobile devices, where computational resources are limited. In this paper we develop CondenseNet, a novel network architecture with unprecedented efficiency. It combines dense connectivity with a novel module called learned group convolution. The dense connectivity facilitates feature re-use in the network, whereas learned group convolutions remove connections between layers for which this feature re-use is superfluous. At test time, our model can be… CONTINUE READING

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