A convolutional neural network with sparse representation

This paper proposes a sparse representation layer in the feature extraction stage of a convolutional neural network (CNN). Our goal is to add sparse transforms to a target network to improve its performance without introducing an extra calculation burden. First, the proposed method was achieved by i...

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Vydané v:	Knowledge-based systems Ročník 209; s. 106419
Hlavní autori:	Yang, Guoan, Yang, Junjie, Lu, Zhengzhi, Liu, Deyang
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	Amsterdam Elsevier B.V 17.12.2020 Elsevier Science Ltd
Predmet:	Algorithms Artificial neural networks Classification Convolutional neural network Extraction Feature extraction Image classification Machine learning Multilayer convolutional sparse coding Networks Neural networks Object recognition Representation Representations Sparse representation Sparse representation Feature extraction Convolutional neural network Multilayer convolutional sparse coding Image classification
ISSN:	0950-7051, 1872-7409
On-line prístup:	Získať plný text
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