Multi-scale Convolution Aggregation and Stochastic Feature Reuse for DenseNets

2 Oct 2018 Mingjie Wang Jun Zhou Wendong Mao Minglun Gong

Recently, Convolution Neural Networks (CNNs) obtained huge success in numerous vision tasks. In particular, DenseNets have demonstrated that feature reuse via dense skip connections can effectively alleviate the difficulty of training very deep networks and that reusing features generated by the initial layers in all subsequent layers has strong impact on performance... (read more)

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