2011
DOI: 10.1093/lpr/mgr006
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Implementation of the likelihood ratio framework for camera identification based on sensor noise patterns

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Cited by 9 publications
(10 citation statements)
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“…We also tested regularized and non-regularized logistic regression fusion of the GMM-UBM scores and the i-vector PLDA scores. 19 Performance was very slightly better than that of the i-vector system alone: C llr was 0.286 and 0.241 for the regularized and non-regularized procedures respectively.…”
Section: Forensic Comparison Of Voice Recordings: Scores From Gmm-ubmmentioning
confidence: 90%
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“…We also tested regularized and non-regularized logistic regression fusion of the GMM-UBM scores and the i-vector PLDA scores. 19 Performance was very slightly better than that of the i-vector system alone: C llr was 0.286 and 0.241 for the regularized and non-regularized procedures respectively.…”
Section: Forensic Comparison Of Voice Recordings: Scores From Gmm-ubmmentioning
confidence: 90%
“…Score-based approaches are increasingly popular across multiple branches of forensic science, e.g., [17][18][19][20][21][22][23][24][25]. Quantitative measurements made on objects of interest such as voice recordings, face images, and glass fragments usually result in multivariate data with complex distributions.…”
Section: Score-based Approaches For the Calculation Of Likelihood Ratmentioning
confidence: 99%
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“…They use the source-anchored method to define non-matches and perform simulations on a set of two camera devices. Van Houten, Alberink and Geradts expanded Nordgaard and Hoglund's experiments to include ten devices [13], also using the source-anchored SLR. We build upon this previous work by considering the trace-anchored SLR, which has not been presented in device identification before.…”
Section: Source-anchored Slr For Camera Device Identificationmentioning
confidence: 99%
“…SLRs were first applied to the camera device identification problem by Nordgaard and Hoglund in 2011 [12]. Van Houten, Alberink, and Geradts wrote a follow-up paper later that year [13]. Both papers only consider the source-anchored definition of non-matches.…”
Section: Introductionmentioning
confidence: 99%