Aggregation Networks for Uncertainty Management

Abstract

In this project, two methodologies for evidence aggregation and information fusion were studied. One methodology uses fuzzy-set-theoretic connectives in a hierarchical network to achieve the fusion. Learning methods for determining the nature and structure of the networks are investigated. The second methodology uses a generalization of the fuzzy integral to achieve the fusion. In addition, various techniques for membership function generation (including fuzzy clustering methods), fuzzy logic inference and morphological edge detection and fusion were investigated.

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Document Details

Document Type
Technical Report
Publication Date
Nov 25, 1991
Accession Number
ADA244399

Entities

People

  • James M. Keller
  • Raghu Krishnapuram

Organizations

  • University of Missouri

Tags

Communities of Interest

  • Energy and Power Technologies
  • Human Systems
  • Materials and Manufacturing Processes

DTIC Thesaurus Topics

  • Air Force
  • Air Force Facilities
  • Artificial Intelligence
  • Change Detection
  • Classification
  • Computer Vision
  • Computers
  • Detection
  • Detectors
  • Fuzzy Logic
  • Fuzzy Sets
  • Information Processing
  • Neural Networks
  • Object Recognition
  • Pattern Recognition
  • Set Theory
  • Target Recognition

Fields of Study

  • Computer science

Readers

  • Artificial Intelligence
  • Computer Vision.

Technology Areas

  • AI & ML
  • AI & ML - Neural Networks