most citedWhen Residual Learning Meets Dense Aggregation: Rethinking the Aggregation of Deep Neural Networks

4 citations · 4 across the 1 of their papers we have counts for

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cs.CV2020★ 4 cited

When Residual Learning Meets Dense Aggregation: Rethinking the Aggregation of Deep Neural Networks

Zhiyu Zhu, Zhen-Peng Bian, Junhui Hou +2

Various architectures (such as GoogLeNets, ResNets, and DenseNets) have been proposed. However, the existing networks usually suffer from either redundancy of convolutional layers…