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Conference Paper/Proceeding/Abstract 1340 views 318 downloads

Local Representation Learning with A Convolutional Autoencoder

Michael P. Kenning, Xianghua Xie Orcid Logo, Michael Edwards, Jingjing Deng

2018 25th IEEE International Conference on Image Processing (ICIP), Pages: 3239 - 3243

Swansea University Authors: Xianghua Xie Orcid Logo, Jingjing Deng

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DOI (Published version): 10.1109/ICIP.2018.8451233

Abstract

We propose a clustering approach embedded in deep convolutional auto-encoder. In contrast to conventional clustering approaches, our method simultaneously learns feature representation and cluster assignment through deep convolutional auto-encoder.

Published in: 2018 25th IEEE International Conference on Image Processing (ICIP)
ISSN: 2381-8549
Published: Athens, Greece 2018 IEEE International Conference on Image Processing 2018
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URI: https://cronfa.swan.ac.uk/Record/cronfa40806
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Abstract: We propose a clustering approach embedded in deep convolutional auto-encoder. In contrast to conventional clustering approaches, our method simultaneously learns feature representation and cluster assignment through deep convolutional auto-encoder.
College: Faculty of Science and Engineering
Start Page: 3239
End Page: 3243

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