The Evaluation of Competing Classifiers

Abstract

This dissertation research makes contributions towards the objective evaluation of competing classifiers, i.e., classification systems (CSs) or pattern recognition algorithms. Automatic CSs have been under development for almost 40 years in a wide range of military and medical applications. During this period, scientists and engineers have developed extensive theory and algorithms for classification, but by comparison have focused little on the testing and evaluation of their systems. Classifier evaluation is very important in the fields of automatic target recognition (ATR) and pilot workload classification. In order for military operators to be confident in new CSs, they must have an objective way of testing and evaluating competing systems.

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Document Details

Document Type
Technical Report
Publication Date
Mar 01, 2000
Accession Number
ADA375294

Entities

People

  • Stephen G. Alsing

Organizations

  • Air Force Institute of Technology

Tags

Communities of Interest

  • C4I
  • Energy and Power Technologies
  • Human Systems
  • Weapons Technologies

DTIC Thesaurus Topics

  • Air Force
  • Data Science
  • Detection
  • Detectors
  • Identification
  • Information Science
  • Machine Learning
  • Pattern Recognition
  • Random Variables
  • Recognition
  • Statistical Algorithms
  • Surveys
  • Synthetic Aperture Radar
  • Target Recognition
  • Test Methods
  • Three Dimensional
  • Two Dimensional

Readers

  • Aerospace Test and Evaluation
  • Computer Vision.
  • Maritime Combat Support and Expeditionary Logistics.

Technology Areas

  • AI & ML