Performances of an ATR System via its ROC Manifold

Abstract

A Classification system such as an Automatic Target Recognition (ATR) system with N possible output labels (or decisions) will have N(N-1) possible errors. The Receiver Operating Characteristic (ROC) manifold was created to quantify all of these errors. Truthed data will produce an approximation to a ROC manifold. How well does the approximate ROC manifold approximate the true ROC manifold? Several functionals exist that quantify the approximation ability, but researchers really wish to quantify the performance in the approximate ROC manifold. This paper will review different performance definitions for ROC curves and manifolds, and thus, quantify the fusion of ATR systems. Examples of different performances will be given that are defined on manifolds.

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Document Details

Document Type
Technical Report
Publication Date
Jul 01, 2008
Accession Number
ADA520526

Entities

People

  • Christine M Schubert
  • Kenneth W. Bauer Jr.
  • Mark E. Oxley
  • Steven N. Thorsen

Organizations

  • Air Force Institute of Technology

Tags

Communities of Interest

  • Autonomy
  • Sensors

DTIC Thesaurus Topics

  • Air Force
  • Air Force Facilities
  • Air Force Research Laboratories
  • Classification
  • Data Sets
  • Detectors
  • Equations
  • Errors
  • Functional Analysis
  • Information Science
  • Machine Learning
  • Mathematics
  • Numbers
  • Probability
  • Real Numbers
  • Statistics
  • Target Recognition

Readers

  • Adaptive Control and Estimation with Uncertainty in Dynamic Systems.
  • Neural Network Machine Learning.
  • Regression Analysis.

Technology Areas

  • AI & ML
  • AI & ML - Machine Learning Algorithms