Fusion of Stochastic and Linguistic Information Using a Conditional Event Framework

Abstract

This report addresses a framework for merging different types and sources of information for applications involving image estimation. Complex decision-making systems rely on feature estimates derived from image data. It is imperative that all available information be used to effectively generate high quality estimates. This information includes stochastic raw sensor data, conditional information obtained from other sources and linguistic information such as if-then rules obtained from human experts who supervise the processing.

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Document Details

Document Type
Technical Report
Publication Date
May 01, 2001
Accession Number
ADA392127

Entities

People

  • Haluk Derin
  • Patrick A. Kelly
  • Wei-bo Gong

Organizations

  • University of Massachusetts Amherst

Tags

Communities of Interest

  • Biomedical
  • Energy and Power Technologies
  • Materials and Manufacturing Processes
  • Sensors

DTIC Thesaurus Topics

  • Adaptive Systems
  • Air Force
  • Air Force Research Laboratories
  • Algorithms
  • Bayesian Networks
  • Computations
  • Data Processing
  • Detectors
  • Graphical User Interface
  • Image Processing
  • Information Science
  • Machine Learning
  • Probability
  • Recognition
  • Signal Processing
  • Target Detection
  • Target Recognition

Fields of Study

  • Computer science

Readers

  • Artificial Intelligence
  • Computer Vision.
  • Defense Acquisition Program Management