ELMAENet: A Simple, Effective and Fast Deep Architecture for Image Classification-Reference-Cited by-同舟云学术

ELMAENet: A Simple, Effective and Fast Deep Architecture for Image Classification

Published:2019-07-23 Issue:1 Volume:51 Page:129-146
ISSN:1370-4621
Container-title:Neural Processing Letters
language:en
Short-container-title:Neural Process Lett

Author:

Chang Peiju,Zhang Jiangshe,Wang Jinyan,Fei Rongrong

Funder

National Basic Research Program

the National Science Foundation of China

First-Class Disciplines Foundation of Ningxia

Publisher

Springer Science and Business Media LLC

Subject

Artificial Intelligence,Computer Networks and Communications,General Neuroscience,Software

Link

http://link.springer.com/content/pdf/10.1007/s11063-019-10079-9.pdf

Reference64 articles.

1. Park DC (2000) Centroid neural network for unsupervised competitive learning. IEEE Trans Neural Netw 11(2):520–528

2. Lee H, Grosse R, Ranganath R, Ng AY (2009) Convolutional deep belief networks for scalable unsupervised learning of hierarchical representations. In: Proceedings of international conference on machine learning

3. Masci J, Meier U, Cirean D, Schmidhuber J (2011) Stacked convolutional auto-encoders for hierarchical feature extraction. In: International conference on artificial neural networks

4. Yim J, Ju J, Jung H, Kim J (2015) Image classification using convolutional neural networks with multi-stage feature. In: Robot intelligence technology and applications 3. Advances in Intelligent Systems and Computing, vol 345. Springer, Cham

5. Krizhevsky A, Sutskever I, Hinton G (2012) ImageNet classification with deep convolutional neural networks. Proc Adv Neural Inf Process Syst 25:1090–1098

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