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Feature Selection for Aiding Glass Forensic Evidence Analysis
Qiang Shen
,
Richard Jensen
Department of Computer Science
Research output
:
Contribution to journal
›
Article
›
peer-review
6
Citations (Scopus)
201
Downloads (Pure)
Overview
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Dive into the research topics of 'Feature Selection for Aiding Glass Forensic Evidence Analysis'. Together they form a unique fingerprint.
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Computer Science
Control
25%
Distribution Group
25%
Estimation Procedure
25%
Evaluation
25%
Expert Knowledge
25%
Feature Selection
50%
Forensic Evidence
25%
Forensics
25%
Likelihood Ratio
100%
Misclassification Rate
25%
Performance Measure
25%
Simulation Mode
25%