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

19 Apr 2020 Zhiyu Zhu Zhen-Peng Bian Junhui Hou Yi Wang Lap-Pui Chau

Various architectures (such as GoogLeNets, ResNets, and DenseNets) have been proposed. However, the existing networks usually suffer from either redundancy of convolutional layers or insufficient utilization of parameters... (read more)

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