VisGraphNet: A complex network interpretation of convolutional neural features-Reference-Cited by-同舟云学术

VisGraphNet: A complex network interpretation of convolutional neural features

Published:2021-01 Issue: Volume:543 Page:296-308
ISSN:0020-0255
Container-title:Information Sciences
language:en
Short-container-title:Information Sciences

Author:

Florindo Joao B.^ORCID,Lee Young-Sup,Jun Kyungkoo,Jeon Gwanggil,Albertini Marcelo K.

Publisher

Elsevier BV

Subject

Artificial Intelligence,Information Systems and Management,Computer Science Applications,Theoretical Computer Science,Control and Systems Engineering,Software

Reference49 articles.

1. Rotation invariant image description with local binary pattern histogram Fourier features;Ahonen,2009

2. Using filter banks in convolutional neural networks for texture classification;Andrearczyk;Pattern Recogn. Lett.,2016

3. Texture analysis and classification: a complex network-based approach;Backes;Inf. Sci.,2013

4. Emergence of scaling in random networks;Barabási;Science,1999

5. Neural Networks for Pattern Recognition;Bishop,1995

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