Densely Connected Convolutional Networks

@article{Huang2017DenselyCC,
  title={Densely Connected Convolutional Networks},
  author={Gao Huang and Zhuang Liu and Kilian Q. Weinberger},
  journal={2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)},
  year={2017},
  pages={2261-2269}
}
Recent work has shown that convolutional networks can be substantially deeper, more accurate, and efficient to train if they contain shorter connections between layers close to the input and those close to the output. [...] Key Method For each layer, the feature-maps of all preceding layers are used as inputs, and its own feature-maps are used as inputs into all subsequent layers. DenseNets have several compelling advantages: they alleviate the vanishing-gradient problem, strengthen feature propagation…Expand
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