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Title: Preliminary Results on Uncertainty Quantification for Pattern Analytics

Abstract

This report summarizes preliminary research into uncertainty quantification for pattern ana- lytics within the context of the Pattern Analytics to Support High-Performance Exploitation and Reasoning (PANTHER) project. The primary focus of PANTHER was to make large quantities of remote sensing data searchable by analysts. The work described in this re- port adds nuance to both the initial data preparation steps and the search process. Search queries are transformed from does the specified pattern exist in the data? to how certain is the system that the returned results match the query? We show example results for both data processing and search, and discuss a number of possible improvements for each.

Authors:
 [1];  [1];  [1];  [1];  [1];  [1];  [1];  [1]
  1. Sandia National Laboratories (SNL-NM), Albuquerque, NM (United States)
Publication Date:
Research Org.:
Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Sandia National Lab. (SNL-CA), Livermore, CA (United States)
Sponsoring Org.:
USDOE National Nuclear Security Administration (NNSA)
OSTI Identifier:
1221712
Report Number(s):
SAND2015-8099
603967
DOE Contract Number:  
AC04-94AL85000
Resource Type:
Technical Report
Country of Publication:
United States
Language:
English

Citation Formats

Stracuzzi, David John, Brost, Randolph, Chen, Maximillian Gene, Malinas, Rebecca, Peterson, Matthew Gregor, Phillips, Cynthia A., Robinson, David G., and Woodbridge, Diane. Preliminary Results on Uncertainty Quantification for Pattern Analytics. United States: N. p., 2015. Web. doi:10.2172/1221712.
Stracuzzi, David John, Brost, Randolph, Chen, Maximillian Gene, Malinas, Rebecca, Peterson, Matthew Gregor, Phillips, Cynthia A., Robinson, David G., & Woodbridge, Diane. Preliminary Results on Uncertainty Quantification for Pattern Analytics. United States. doi:10.2172/1221712.
Stracuzzi, David John, Brost, Randolph, Chen, Maximillian Gene, Malinas, Rebecca, Peterson, Matthew Gregor, Phillips, Cynthia A., Robinson, David G., and Woodbridge, Diane. Tue . "Preliminary Results on Uncertainty Quantification for Pattern Analytics". United States. doi:10.2172/1221712. https://www.osti.gov/servlets/purl/1221712.
@article{osti_1221712,
title = {Preliminary Results on Uncertainty Quantification for Pattern Analytics},
author = {Stracuzzi, David John and Brost, Randolph and Chen, Maximillian Gene and Malinas, Rebecca and Peterson, Matthew Gregor and Phillips, Cynthia A. and Robinson, David G. and Woodbridge, Diane},
abstractNote = {This report summarizes preliminary research into uncertainty quantification for pattern ana- lytics within the context of the Pattern Analytics to Support High-Performance Exploitation and Reasoning (PANTHER) project. The primary focus of PANTHER was to make large quantities of remote sensing data searchable by analysts. The work described in this re- port adds nuance to both the initial data preparation steps and the search process. Search queries are transformed from does the specified pattern exist in the data? to how certain is the system that the returned results match the query? We show example results for both data processing and search, and discuss a number of possible improvements for each.},
doi = {10.2172/1221712},
journal = {},
number = ,
volume = ,
place = {United States},
year = {Tue Sep 01 00:00:00 EDT 2015},
month = {Tue Sep 01 00:00:00 EDT 2015}
}

Technical Report:

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