An application of case-based reasoning with machine learning for forensic autopsy-Reference-Cited by-同舟云学术

An application of case-based reasoning with machine learning for forensic autopsy

Published:2014-06 Issue:7 Volume:41 Page:3497-3505
ISSN:0957-4174
Container-title:Expert Systems with Applications
language:en
Short-container-title:Expert Systems with Applications

Author:

Yeow Wei Liang,Mahmud Rohana^ORCID,Raj Ram Gopal

Publisher

Elsevier BV

Subject

Artificial Intelligence,Computer Science Applications,General Engineering

Reference34 articles.

1. Case-based reasoning: Foundational issues, methodological variations, and system approaches;Aamodt;AI Communications,1994

2. Exact solutions to Bayesian and maximum likelihood problems in facial identification when population and error distributions are known;Allen;Forensic Science International,2008

3. ASTIS. (2012). .

4. Post-retrieval search hit clustering to improve information retrieval effectiveness: Two digital forensics case studies;Beebe;Decision Support Systems,2011

5. Classification of physiological signals for wheel loader operators using multi-scale entropy analysis and case-based reasoning;Begum;Expert Systems with Applications,2013

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