Preliminary Neural Network Detection of a Gulf Stream in Images of Sea Surface Temperature Gradients. Phase 1

Abstract

A concept is tested for automatically identifying Gulf Stream surface temperature gradients among the myriad fronts discernable as edges in satellite infrared imagery. The concept is to use the techniques of neural networks in concert with a principal component climatology of Gulf Stream axes. Sample neural networks were constructed that successfully produced mode coefficients for the first three components for a large set of well defined Gulf Streams. One network, operating on a jumble of edges from a real composite sea surface temperature image, produced a 3-mode Gulf Stream sufficiently close to the actual Gulf Stream edges as to hold promise for identifying the Gulf Stream's gradients automatically.

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Document Details

Document Type
Technical Report
Publication Date
Apr 28, 1989
Accession Number
ADA207801

Entities

People

  • Eugene J. Molinelli
  • Michael J. Flanigan

Tags

Communities of Interest

  • Space

DTIC Thesaurus Topics

  • C Programming Language
  • Change Detection
  • Computer Programming
  • Computer Programs
  • Computers
  • Data Analysis
  • Detection
  • Detectors
  • Digital Information
  • Military Research
  • Neural Networks
  • Operating Systems
  • Pattern Recognition
  • Satellite Imaging
  • Sea Surface Temperature
  • Surface Temperature
  • Temperature Gradients

Readers

  • Atmospheric Science / Meteorology, specifically Wind Wave Turbulence.
  • Neural Network Machine Learning.
  • Oceanography.

Technology Areas

  • AI & ML
  • AI & ML - Neural Networks
  • Space