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                            Funding & Awards
 Application of Machine Learning to Toolmarks: Statistically Based Methods for Impression Pattern Comparisons
Award Information
Awardee
              Research Foundation of CUNY c/o John Jay College
Award #
              2009-DN-BX-K041
Funding Category
              Competitive
Location
                    New York, NY
Congressional District
              10
Status
              Closed
Funding First Awarded
              2009
Total funding (to date)
              $704,189
Original Solicitation
              NIJ FY 09 Research and Development in Forensic Analysis of Impression Evidence:  Invited Full Proposals
Description of original award (Fiscal Year 2009, $704,189)
The authors propose to develop standardized methodologies to study and critically evaluate impression evidence.  Three-dimensional vector data of the cartridge case impressions will be collected using high resolution 3D laser scanning and stored in a large database. This will generate a digital 3-dimensional map of the impression surface using X, Y, and Z coordinates. The data will then be examined with multiple multivariate statistical methods in order to quantify the criteria necessary to match a physical marking.

ca/ncf



  
Grant-Funded Publications
        
                      Forensic Surface Metrology: Tool Mark Evidence
                  Application of Machine Learning to Toolmarks: Statistically Based Methods for Impression Pattern Comparisons

  
Date Created: September 22, 2009
    
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