Robust Detection, Discrimination, and Remediation of UXO: Statistical Signal Processing Approaches to Address Uncertainties Encountered in Field Test Scenarios SERDP Project MR-1663

Abstract

The objective of this work was to develop methodologies that will allow the human analyst to be removed from the processing loop. It has been shown in a number of recent demonstrations that when the most skilled practitioners process geophysical data, select data chips for analysis, select features for classification, select one of a suite of classifiers, and manually tune the classifier boundaries, excellent classification performance can be achieved. Here, we aim to develop techniques to improve target characterization and reduce classifier sensitivity to imprecision in the target characterizations, thereby reducing the need for an expert human analyst.

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Document Details

Document Type
Technical Report
Publication Date
Jan 03, 2012
Accession Number
ADA557406

Entities

People

  • Leslie M. Collins

Organizations

  • Duke University

Tags

Communities of Interest

  • Human Systems
  • Materials and Manufacturing Processes
  • Sensors

DTIC Thesaurus Topics

  • Algorithms
  • Boundaries
  • Classification
  • Data Science
  • Data Sets
  • Demonstrations
  • Detection
  • Detectors
  • Discrimination
  • Electromagnetic Induction
  • Field Tests
  • Machine Learning
  • Sensitivity
  • Signal Processing
  • Supervised Machine Learning
  • Synthetic Aperture Radar
  • Unexploded Ammunition

Readers

  • Computational Modeling and Simulation
  • Military/Explosive Ordnance Disposal (EOD) Technology
  • Neural Network Machine Learning.