Neural Network-Based Hyperspectral Algorithms

Abstract

Our long term goal is to contribute to our understanding of numerical methods for inversion of remotely sensed data, and to adapt these methods to the retrieval of water parameters from hyperspectral observations of complex coastal environments.

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Document Details

Document Type
Technical Report
Publication Date
Sep 30, 1999
Accession Number
ADA631005

Entities

People

  • Grayson H. Rayborn
  • Ronald J. Holyer

Organizations

  • University of Southern Mississippi

Tags

Communities of Interest

  • Space

DTIC Thesaurus Topics

  • Algorithms
  • Artificial Intelligence Computing
  • Artificial Intelligence Software
  • Bathymetry
  • Computational Processes
  • Computing-Related Activities
  • Data Compression
  • Data Sets
  • Errors
  • Neural Networks
  • Observation
  • Optical Properties
  • Radiance
  • Radiative Transfer
  • Reflectance
  • Remote Sensing
  • Training

Fields of Study

  • Environmental science

Readers

  • Coastal Oceanography
  • Neural Network Machine Learning.

Technology Areas

  • AI & ML
  • AI & ML - Neural Networks