Predicting suitability of finger marks using machine learning techniques and examiner annotations

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State: Public
Version: author
License: CC BY-NC-ND 4.0
Serval ID
serval:BIB_4C4B618FFB2D
Type
Article: article from journal or magazin.
Collection
Publications
Institution
Title
Predicting suitability of finger marks using machine learning techniques and examiner annotations
Journal
Forensic Science International
Author(s)
Eldridge Heidi, De Donno Marco, Champod Christophe
ISSN
0379-0738
Publication state
Published
Issued date
03/2021
Volume
320
Pages
110712
Language
english
Keywords
Pathology and Forensic Medicine
Open Access
Yes
Funding(s)
University of Lausanne
Create date
17/02/2021 10:14
Last modification date
18/02/2021 7:28
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