Classification of Selected Radar Imagery Patterns Using a Binary Tree Classifier.

Abstract

This report details the results of classifying radar imagery using a binary tree classifier. It was found that this classification algorithm works well with radar imagery, which would indicate a normal (Gaussian) feature vector distribution. The number of elements in each feature vector is the limiting factor, classification time is negligible once the tree structure has been created. Keywords: Binary decision tree; Bayes classifier; Radar imagery; and Feature selection.

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Document Details

Document Type
Technical Report
Publication Date
Oct 01, 1986
Accession Number
ADA183370

Entities

People

  • Neil D. Fox

Organizations

  • Geospatial Research Laboratory

Tags

Communities of Interest

  • C4I

DTIC Thesaurus Topics

  • Accuracy
  • Algorithms
  • Artificial Intelligence
  • Classification
  • Covariance
  • Engineers
  • Feature Extraction
  • Feature Selection
  • Fresh Water
  • High Resolution
  • Images
  • Machine Learning
  • North Carolina
  • Pattern Recognition
  • Procedures (Computers)
  • Radar
  • Trees (Data Structures)

Fields of Study

  • Computer science

Readers

  • Computer Vision.
  • Radar Systems Engineering.