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	Relay Backpropagation for Effective Learning of Deep Convolutional Neural Networks
	Shen, Li ; Lin, Zhouchen ; Huang, Qingming
	2016
关键词	Relay Backpropagation Convolutional neural networks Large scale image classification
英文摘要	Learning deeper convolutional neural networks has become a tendency in recent years. However, many empirical evidences suggest that performance improvement cannot be attained by simply stacking more layers. In this paper, we consider the issue from an information theoretical perspective, and propose a novel method Relay Backpropagation, which encourages the propagation of effective information through the network in training stage. By virtue of the method, we achieved the first place in ILSVRC 2015 Scene Classification Challenge. Extensive experiments on two large scale challenging datasets demonstrate the effectiveness of our method is not restricted to a specific dataset or network architecture.; CPCI-S(ISTP); lishen@robots.ox.ac.uk; zlin@pku.edu.cn; qmhuang@ucas.ac.cn; 467-482; 9911
语种	英语
出处	14th European Conference on Computer Vision (ECCV)
DOI标识	10.1007/978-3-319-46478-7_29
内容类型	其他
源URL	[http://ir.pku.edu.cn/handle/20.500.11897/460047]
专题	信息科学技术学院
推荐引用方式 GB/T 7714	Shen, Li,Lin, Zhouchen,Huang, Qingming. Relay Backpropagation for Effective Learning of Deep Convolutional Neural Networks. 2016-01-01.

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