Neural Network Retinal Model Real Time Implementation

Abstract

The solution of complex image processing problems, both military and commercial are expected to benefit significantly from research onto biological vision systems. However, current development of biological models of vision are hampered by lack of low-cost, high-performance, computing hardware that addresses the specific needs of vision processing. The goal of this SBIR Phase I project has been to take a significant neural network vision application and to map it onto dedicated hardware for real time implementation. The neural network was already demonstrated using software simulation on a general purpose computer. During Phase 1, HNC took a neural network model of the retina and, using HNC's Vision Processor (ViP) prototype hardware, achieved a speedup factor of 200 over the retina algorithm executed on the Sun SPARCstation. A performance enhancement of this magnitude on a very general model demonstrates that the door is open to a new generation of vision research and applications. The model is described along with the digital hardware implementation of the algorithm using the new ViP chip set.

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Document Details

Document Type
Technical Report
Publication Date
Sep 02, 1992
Accession Number
ADA255652

Entities

People

  • Robert W. Means

Tags

Communities of Interest

  • Sensors

DTIC Thesaurus Topics

  • Algorithms
  • Arithmetic
  • Artificial Intelligence Computing
  • Artificial Intelligence Software
  • Computers
  • Convolution
  • Couplings
  • Detection
  • Detectors
  • Diagrams
  • Dimensionality Reduction
  • Image Processing
  • Networks
  • Neural Networks
  • Noise Reduction
  • Signal Processing
  • Two Dimensional

Fields of Study

  • Computer science

Readers

  • Neural Network Machine Learning.
  • Parallel and Distributed Computing.
  • Vision Science/Vision Psychology/Cognitive Neuroscience.

Technology Areas

  • AI & ML
  • AI & ML - Neural Networks