Non-parametric classification algorithm with an unknown class

B.G.H. Gorte, N. Gorte-Kroupnova

Research output: Chapter in Book/Report/Conference proceedingConference contributionAcademicpeer-review

7 Citations (Scopus)
19 Downloads (Pure)

Abstract

In the classification of pixels of a multispectral image by methods of supervised classification, a problem can arise in case when an unknown class is present. In this paper, we suggest a method that gives good results in such a case. The method provides an estimation for a posteriori probability vectors (and consequently, classification), and, besides, estimates the prior probability of classes, including the unknown one, and thus, the areas occupied by every class.
Original languageEnglish
Title of host publicationProceedings of International Symposium on Computer Vision - ISCV 1995
Place of PublicationLos Alamitos, CA
PublisherIEEE
Pages443-448
Number of pages6
ISBN (Print)0-8186-7190-4
DOIs
Publication statusPublished - 1995
EventIEEE International Symposium on Computer Vision 1995 - Coral Gables, United States
Duration: 21 Nov 199523 Nov 1995

Conference

ConferenceIEEE International Symposium on Computer Vision 1995
Country/TerritoryUnited States
CityCoral Gables
Period21/11/9523/11/95

Keywords

  • ADLIB-ART-568
  • EOS

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