No Cover Image

Conference contribution 150 views

Local Representation Learning with A Convolutional Autoencoder / Michael P. Kenning; Xianghua Xie; Michael Edwards; Jingjing Deng

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

Swansea University Author: Xie, Xianghua

  • Accepted Manuscript under embargo until: 7th October 2019

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
Online Access: Check full text

URI: https://cronfa.swan.ac.uk/Record/cronfa40806
Tags: Add Tag
No Tags, Be the first to tag this record!
first_indexed 2018-06-23T19:33:39Z
last_indexed 2018-09-24T18:51:22Z
id cronfa40806
recordtype SURis
fullrecord <?xml version="1.0"?><rfc1807><datestamp>2018-09-24T16:20:42Z</datestamp><bib-version>v2</bib-version><id>40806</id><entry>2018-06-23</entry><title>Local Representation Learning with A Convolutional Autoencoder</title><alternativeTitle></alternativeTitle><author>Xianghua Xie</author><firstname>Xianghua</firstname><surname>Xie</surname><active>true</active><ORCID>0000-0002-2701-8660</ORCID><ethesisStudent>false</ethesisStudent><sid>b334d40963c7a2f435f06d2c26c74e11</sid><email>53b7e8cec1e3c035df428f36f80bdea5</email><emailaddr>ulOdsUw0nzyNlMFzZoDyVp320YwKTXZRCaAvm14NMEw=</emailaddr><date>2018-06-23</date><deptcode>SCS</deptcode><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.</abstract><type>Conference contribution</type><journal>2018 25th IEEE International Conference on Image Processing (ICIP)</journal><volume/><journalNumber/><paginationStart>3239</paginationStart><paginationEnd>3243</paginationEnd><publisher>2018 IEEE International Conference on Image Processing</publisher><placeOfPublication>Athens, Greece</placeOfPublication><isbnPrint/><isbnElectronic/><issnPrint/><issnElectronic>2381-8549</issnElectronic><keywords></keywords><publishedDay>7</publishedDay><publishedMonth>10</publishedMonth><publishedYear>2018</publishedYear><publishedDate>2018-10-07</publishedDate><doi>10.1109/ICIP.2018.8451233</doi><url>https://ieeexplore.ieee.org/document/8451233/</url><notes></notes><college>College of Science</college><department>Computer Science</department><CollegeCode>CSCI</CollegeCode><DepartmentCode>SCS</DepartmentCode><institution/><researchGroup>Visual Computing</researchGroup><supervisor/><sponsorsfunders/><grantnumber/><degreelevel/><degreename>None</degreename><lastEdited>2018-09-24T16:20:42Z</lastEdited><Created>2018-06-23T15:46:38Z</Created><path><level id="1">College of Science</level><level id="2">Computer Science</level></path><authors><author><firstname>Michael P.</firstname><surname>Kenning</surname><orcid/><order>1</order></author><author><firstname>Xianghua</firstname><surname>Xie</surname><orcid/><order>2</order></author><author><firstname>Michael</firstname><surname>Edwards</surname><orcid/><order>3</order></author><author><firstname>Jingjing</firstname><surname>Deng</surname><orcid/><order>4</order></author></authors><documents><document><filename>Under embargo</filename><originalFilename>Under embargo</originalFilename><uploaded>2018-06-23T15:47:37Z</uploaded><type>Output</type><contentLength>921994</contentLength><contentType>application/pdf</contentType><version>AM</version><cronfaStatus>true</cronfaStatus><action>Updated Copyright</action><actionDate>10/09/2018</actionDate><embargoDate>2019-10-07T00:00:00</embargoDate><documentNotes/><copyrightCorrect>true</copyrightCorrect><language>eng</language></document></documents></rfc1807>
spelling 2018-09-24T16:20:42Z v2 40806 2018-06-23 Local Representation Learning with A Convolutional Autoencoder Xianghua Xie Xianghua Xie true 0000-0002-2701-8660 false b334d40963c7a2f435f06d2c26c74e11 53b7e8cec1e3c035df428f36f80bdea5 ulOdsUw0nzyNlMFzZoDyVp320YwKTXZRCaAvm14NMEw= 2018-06-23 SCS 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. Conference contribution 2018 25th IEEE International Conference on Image Processing (ICIP) 3239 3243 2018 IEEE International Conference on Image Processing Athens, Greece 2381-8549 7 10 2018 2018-10-07 10.1109/ICIP.2018.8451233 https://ieeexplore.ieee.org/document/8451233/ College of Science Computer Science CSCI SCS Visual Computing None 2018-09-24T16:20:42Z 2018-06-23T15:46:38Z College of Science Computer Science Michael P. Kenning 1 Xianghua Xie 2 Michael Edwards 3 Jingjing Deng 4 Under embargo Under embargo 2018-06-23T15:47:37Z Output 921994 application/pdf AM true Updated Copyright 10/09/2018 2019-10-07T00:00:00 true eng
title Local Representation Learning with A Convolutional Autoencoder
spellingShingle Local Representation Learning with A Convolutional Autoencoder
Xie, Xianghua
title_short Local Representation Learning with A Convolutional Autoencoder
title_full Local Representation Learning with A Convolutional Autoencoder
title_fullStr Local Representation Learning with A Convolutional Autoencoder
title_full_unstemmed Local Representation Learning with A Convolutional Autoencoder
title_sort Local Representation Learning with A Convolutional Autoencoder
author_id_str_mv b334d40963c7a2f435f06d2c26c74e11
author_id_fullname_str_mv b334d40963c7a2f435f06d2c26c74e11_***_Xie, Xianghua
author Xie, Xianghua
author2 Michael P. Kenning
Xianghua Xie
Michael Edwards
Jingjing Deng
format Conference contribution
container_title 2018 25th IEEE International Conference on Image Processing (ICIP)
container_start_page 3239
publishDate 2018
institution Swansea University
issn 2381-8549
doi_str_mv 10.1109/ICIP.2018.8451233
publisher 2018 IEEE International Conference on Image Processing
college_str College of Science
hierarchytype
hierarchy_top_id collegeofscience
hierarchy_top_title College of Science
hierarchy_parent_id collegeofscience
hierarchy_parent_title College of Science
department_str Computer Science{{{_:::_}}}College of Science{{{_:::_}}}Computer Science
url https://ieeexplore.ieee.org/document/8451233/
document_store_str 0
active_str 1
researchgroup_str Visual Computing
description 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_date 2018-10-07T04:42:59Z
_version_ 1628770066705154048
score 10.79796