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Project Topic |
Sponsor |
 |
Eliminating Crew Noise
in Marine Seismic Surveys using Neural Networks
|
CGG, Inc. Houston, Texas
|
|
Seismic Attribute Analysis
Using Neural Networks
|
NSF
|
|
Solving Environmental Problems
Using Geomechanics and Geophysics
|
NSF
|
|
Interpreting IP response in
TEM data using neural networks
|
NSF / US-Egypt Joint Science
Technology Board
|
|
Interpretation of geological
data sets of the Bongara Area of Northern Peru
|
Fullbright Program
|
|
Mesoscale predictablility
and improvement of ensemble forecasts and predictions using neural networks
|
Office of Naval Research
|
|
Automated warning system for
lahar flows using GIS
|
NASA
|
|
Neural network interpretation
of wireline logs |
Baker Atlas |
|
Neural network feasibility
study using Dig-face characterization data |
Lockheed Idaho Technologies
Co. |
|
High-resolution
subsurface imaging and neural network recognition for non-intrusive buried
substance location |
DOE |
|
:Identifying subsidence
hazards with a unique high-resolution EM system and neural network interpretation |
US Bureau of Mines |
|
Subsurface void
detection with a unique high-resolution EM system and neural network interpretation |
US Army |
|
Study of gold and
copper mineral deposit classes using neural networks |
UA Foundation |
|
Estimation of moisture
content of mine tailings from spectral reflectance values for prediction
of blowing dust hazard. |
US Bureau of Mines |