Automated Acquisition of Object Recognition Strategies for Image Exploitation.

Abstract

This effort attempts to solve a crucial problem of knowledge-based scene interpretation by building proper, more efficient, recognition strategies. The proposed system will automatically learn object recognition strategies with the goal of learning how to recognize objects from a combination of training images and a library of visual sources. This project will incorporate two types of learning techniques, Hypothesis Generation Learning, and Hypothesis Verification. Recognition graphs will represent three control strategies: an exhaustive exploration algorithm, a DNF generalization algorithm, and a graph optimization algorithm.

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Document Details

Document Type
Technical Report
Publication Date
Aug 01, 1995
Accession Number
ADA299588

Entities

People

  • Allen R. Hanson
  • Bruce A. Draper
  • Edward M. Riseman

Organizations

  • University of Massachusetts Amherst

Tags

DTIC Thesaurus Topics

  • Acquisition
  • Algorithms
  • Computer Vision
  • Demographic Cohorts
  • Heuristic Methods
  • Identification
  • Image Processing
  • Image Recognition
  • Learning
  • Mathematics
  • Object Recognition
  • Optimization
  • Recognition
  • Training
  • Verification

Readers

  • Artificial Intelligence
  • Computer Vision.
  • Neural Network Machine Learning.