Cloud Data Set for Neural Network Classification Studies

Abstract

A large set of GOES imagery has been analyzed to generate a cloud data set for neural network classification studies. The classification scheme uses 13 classes of clouds. The cloud data base is large enough to allow cross- validation tests of automated cloud classification techniques. The methods used to acquire the data on cloud type and a brief overview of the planned automated classification experiments are presented. The appendix contains an inventory of the cloud data set.

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Document Details

Document Type
Technical Report
Publication Date
Jan 23, 1992
Accession Number
ADA256181

Entities

People

  • Ira G. Smotroff
  • K. F. Heideman
  • Rupert S. Hawkins

Organizations

  • Phillips Laboratory

Tags

Communities of Interest

  • Sensors
  • Space

DTIC Thesaurus Topics

  • Abstracts
  • Algorithms
  • Artificial Intelligence Computing
  • Artificial Intelligence Software
  • Artificial Satellites
  • Computer Programs
  • Data Science
  • Data Sets
  • Databases
  • Information Science
  • Inventory
  • Machine Learning
  • Meteorological Satellites
  • Network Science
  • Neural Networks
  • Standards
  • Validation

Readers

  • Atmospheric Science/Meteorology
  • Neural Network Machine Learning.
  • Systems Analysis and Design

Technology Areas

  • AI & ML
  • AI & ML - Neural Networks