Use of Model-Segmentation Criteria in Clustering and Segmentation of Time Series and Digital Images.

Abstract

This paper treats the development and use of criteria for model selection, particularly for the choice of the number of groups ( clusters ) in the analysis of multivariate data and of the number of classes of segments in the segmentation of time series and digital images. Criteria such as those of Akaike, Schwarz and Kashyap are considered. (Author)

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Document Details

Document Type
Technical Report
Publication Date
May 05, 1983
Accession Number
ADA128840

Entities

People

  • Stanley L. Sclove

Organizations

  • University of Illinois at Chicago

Tags

Communities of Interest

  • Materials and Manufacturing Processes

DTIC Thesaurus Topics

  • Abstracts
  • Algorithms
  • Bibliographies
  • Business Administration
  • Clustering
  • Computer Programs
  • Computer Vision
  • Contracts
  • Data Analysis
  • Digital Images
  • Illinois
  • Image Segmentation
  • Military Research
  • Probability
  • Simulations
  • United States
  • Universities

Fields of Study

  • Mathematics

Readers

  • Computer Vision.
  • Statistical inference.