•  English
    • Persian
    • English
  •   Login
  • Ferdowsi University of Mashhad
  • |
  • Information Center and Central Library
    • Persian
    • English
  • Home
  • Source Types
    • Journal Paper
    • Ebook
    • Conference Paper
    • Standard
    • Protocol
    • Thesis
  • Use Help
View Item 
  •   FUM Digital Library
  • Fum
  • Articles
  • Latin Articles
  • View Item
  •   FUM Digital Library
  • Fum
  • Articles
  • Latin Articles
  • View Item
  • All Fields
  • Title
  • Author
  • Year
  • Publisher
  • Subject
  • Publication Title
  • ISSN
  • DOI
  • ISBN
Advanced Search
JavaScript is disabled for your browser. Some features of this site may not work without it.

Semi-supervised metric learning via topology preserving multiple semi-supervised assumptions

Author:
Qianying Wang
,
Pong C Yuen
,
Guocan Feng
Year
: 2013
DOI: 10.1016/j.patcog.2013.02.015
URI: http://libsearch.um.ac.ir:80/fum/handle/fum/558772
Collections :
  • Latin Articles
  • Download: (648.1Kb)
  • Show Full MetaData Hide Full MetaData
  • Statistics

    Semi-supervised metric learning via topology preserving multiple semi-supervised assumptions

Show full item record

contributor authorQianying Wang
contributor authorPong C Yuen
contributor authorGuocan Feng
date accessioned2020-03-11T14:21:25Z
date available2020-03-11T14:21:25Z
date issued2013
identifier otherXHceyMo7324enuYVxjbBLa3n5aVCZcmuHc3egTrb43J0eEMHS7.pdf
identifier urihttp://libsearch.um.ac.ir:80/fum/handle/fum/558772?locale-attribute=en
formatgeneral
languageEnglish
titleSemi-supervised metric learning via topology preserving multiple semi-supervised assumptions
typeJournal Paper
contenttypeFulltext
contenttypeFulltext
identifier padid4354088
identifier doi10.1016/j.patcog.2013.02.015
journal titlePattern Recognition
coverageAcademic
pages2576-2587
journal volume46
journal issue9
filesize663473
citations3
  • About Us
نرم افزار کتابخانه دیجیتال "دی اسپیس" فارسی شده توسط یابش برای کتابخانه های ایرانی | تماس با یابش
DSpace software copyright © 2019-2022  DuraSpace