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Feb, 2018
交替更新团块的卷积神经网络
Convolutional Neural Networks with Alternately Updated Clique
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Yibo Yang, Zhisheng Zhong, Tiancheng Shen, Zhouchen Lin
TL;DR
提出了一种基于循环反馈结构和多尺度特征策略的CliqueNet卷积神经网络,通过改进信息流提高了网络的训练效率,利用参数更加高效,实验结果在CIFAR-10,CIFAR-100,SVHN和ImageNet等数据集上表现优异,同时参数规模更小。
Abstract
Improving
information flow
in deep networks helps to ease the training difficulties and utilize parameters more efficiently. Here we propose a new
convolutional neural network
architecture with alternately update
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