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Title: Visual cluster analysis and pattern recognition methods

Abstract

A method of clustering using a novel template to define a region of influence. Using neighboring approximation methods, computation times can be significantly reduced. The template and method are applicable and improve pattern recognition techniques.

Inventors:
 [1];  [1]
  1. Albuquerque, NM
Publication Date:
Research Org.:
AT&T
OSTI Identifier:
874064
Patent Number(s):
US 6304675
Assignee:
Sandia Corporation (Albuquerque, NM)
DOE Contract Number:  
AC04-76DP00789
Resource Type:
Patent
Country of Publication:
United States
Language:
English
Subject:
visual; cluster; analysis; pattern; recognition; methods; method; clustering; novel; template; define; region; influence; neighboring; approximation; computation; times; significantly; reduced; applicable; improve; techniques; pattern recognition; significantly reduce; /382/

Citation Formats

Osbourn, Gordon Cecil, and Martinez, Rubel Francisco. Visual cluster analysis and pattern recognition methods. United States: N. p., 2001. Web.
Osbourn, Gordon Cecil, & Martinez, Rubel Francisco. Visual cluster analysis and pattern recognition methods. United States.
Osbourn, Gordon Cecil, and Martinez, Rubel Francisco. 2001. "Visual cluster analysis and pattern recognition methods". United States. https://www.osti.gov/servlets/purl/874064.
@article{osti_874064,
title = {Visual cluster analysis and pattern recognition methods},
author = {Osbourn, Gordon Cecil and Martinez, Rubel Francisco},
abstractNote = {A method of clustering using a novel template to define a region of influence. Using neighboring approximation methods, computation times can be significantly reduced. The template and method are applicable and improve pattern recognition techniques.},
doi = {},
url = {https://www.osti.gov/biblio/874064}, journal = {},
number = ,
volume = ,
place = {United States},
year = {2001},
month = {1}
}

Works referenced in this record:

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A memory efficient semi-Naive Bayes classifier with grouping of cases
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Texture analysis and segmentation of seismic images
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