Application of Neural Networks to Large-Scale Cloud Pattern Recognition

Abstract

A Multi-layer Perceptron Neural Network methodology is used to classify eight types of large-scale cloud patterns. The data are taken from GOES-W visible images from Oct. 1-Dec. 31, 1983. Large-scale features are previously identified by a human expert to provide a data set for supervised learning. Discriminant Analysis is used to reduce the set of network inputs and as a comparison classification methodology. In three different tests, the neural network technique classifies the cases with consistently higher accuracy than Discriminant Analysis. The problem of image segmentation is addressed in a preliminary test of the Hierarchical Stepwise Optimization algorithm.

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Document Details

Document Type
Technical Report
Publication Date
Mar 01, 1991
Accession Number
ADA238986

Entities

People

  • J. E. Peak

Organizations

  • Computer Sciences Corporation

Tags

Communities of Interest

  • Energy and Power Technologies
  • Space

DTIC Thesaurus Topics

  • Accuracy
  • Algorithms
  • Artificial Intelligence
  • Artificial Intelligence Software
  • Computer Programs
  • Computer Science
  • Computer Vision
  • Data Sets
  • Discriminant Analysis
  • Gray Scale
  • Image Segmentation
  • Information Science
  • Neural Networks
  • Pattern Recognition
  • Plastic Explosives
  • Statistical Analysis
  • Supervised Machine Learning

Fields of Study

  • Computer science

Readers

  • Atmospheric Remote Sensing.
  • Computational Modeling and Simulation
  • Neural Network Machine Learning.

Technology Areas

  • AI & ML
  • AI & ML - Neural Networks