Artificial Neural Networks to Extract Optical Properties of Marine Microorganisms from Their Mueller Scattering Matrix

Abstract

The long term goals of this project are to understand and quantify light scattering from ensembles of both spherical and non-spherical objects in ocean water, to characterize the effect of ensembles of micro-organisms and inorganic particulates on the propagation of polarized light through sea water, and to assess the feasibility of computer simulated artificial neural network to extract optical properties of marine particulates from polarized light scattering measurements.

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Document Details

Document Type
Technical Report
Publication Date
Jan 01, 1998
Accession Number
ADA551594

Entities

People

  • Patricia G. Hull

Organizations

  • Tennessee State University

Tags

Communities of Interest

  • Energy and Power Technologies

DTIC Thesaurus Topics

  • Absorption Coefficients
  • Coefficients
  • Computer Programming
  • Computer Programs
  • Computers
  • Light Scattering
  • Mainframe Computers
  • Microorganisms
  • Neural Networks
  • Normal Distribution
  • Optical Properties
  • Parallel Computing
  • Parallel Processing
  • Particle Size
  • Particles
  • Refractive Index
  • Scattering

Fields of Study

  • Environmental science

Readers

  • Aerosol Science/Aerosol Physics
  • Image Processing and Computer Vision.
  • Ocean-Atmosphere Mesoscale Modeling, Data Assimilation, and Flux Boundary Layers

Technology Areas

  • AI & ML
  • AI & ML - Neural Networks