Optical Neural Nets for Scene Analysis

Abstract

A hybrid optical/digital neural net for scene an analysis described. It combines pattern recognition and neural net techniques. New algorithms, architectures and applications are described for optimization neural nets (a mixture neural net for image spectrometry, cubic and quadratic neural nets for multitarget tracking, and a matrix inversion neural net), production system neural nets, symbolic neural nets and a new adaptive learning neural net (the adaptive clustering neural net). Progress in the first six months on these seven neural nets and our hardware are presented. Keywords: Artificial intelligence, Computer architecture, Networks, Data bases, Data processing. (AW)

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Document Details

Document Type
Technical Report
Publication Date
Oct 23, 1989
Accession Number
ADA213986

Entities

People

  • David Cassent

Organizations

  • Carnegie Mellon University

Tags

Communities of Interest

  • Energy and Power Technologies
  • Human Systems
  • Sensors
  • Space
  • Weapons Technologies

DTIC Thesaurus Topics

  • Abstracts
  • Algorithms
  • Classification
  • Clustering
  • Computer Vision
  • Contracts
  • Correlators
  • Data Processing
  • Image Processing
  • Inversion
  • Learning
  • Multitarget Tracking
  • Optimization
  • Pattern Recognition
  • Production
  • Recognition
  • Security

Fields of Study

  • Computer science

Readers

  • Neural Network Machine Learning.

Technology Areas

  • AI & ML
  • AI & ML - Neural Networks