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Rudolf Haraksim
Rudolf Haraksim
Verified email at ec.europa.eu
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Cited by
Year
A guideline for the validation of likelihood ratio methods used for forensic evidence evaluation
D Meuwly, D Ramos, R Haraksim
Forensic science international 276, 142-153, 2017
1712017
Faceqnet: Quality assessment for face recognition based on deep learning
J Hernandez-Ortega, J Galbally, J Fierrez, R Haraksim, L Beslay
2019 International Conference on Biometrics (ICB), 1-8, 2019
1602019
A study of age and ageing in fingerprint biometrics
J Galbally, R Haraksim, L Beslay
IEEE Transactions on Information Forensics and Security 14 (5), 1351-1365, 2018
812018
Measuring coherence of computer-assisted likelihood ratio methods
R Haraksim, D Ramos, D Meuwly, CEH Berger
Forensic Science International 249, 123-132, 2015
382015
Likelihood ratio data to report the validation of a forensic fingerprint evaluation method
D Ramos, R Haraksim, D Meuwly
Data in brief 10, 75-92, 2017
362017
Validation of forensic automatic likelihood ratio methods
D Ramos, D Meuwly, R Haraksim, CEH Berger
Handbook of forensic statistics, 143-162, 2020
282020
Fingerprint growth model for mitigating the ageing effect on children’s fingerprints matching
R Haraksim, J Galbally, L Beslay
Pattern Recognition 88, 614-628, 2019
212019
Investigation of portability of space docking techniques for autonomous underwater docking
F Maurelli, Y Petillot, A Mallios, S Krupinski, R Haraksim, P Sotiropoulos
OCEANS 2009-EUROPE, 1-9, 2009
182009
Study on face identification technology for its implementation in the Schengen information system
J Galbally, P Ferrara, R Haraksim, A Psyllos, L Beslay
Publications Office of the European Union, 2019
142019
Validation of likelihood ratio methods used for forensic evidence evaluation: application in forensic fingerprints
R Haraksim
142014
Biometric evidence in forensic automatic speaker recognition
A Drygajlo, R Haraksim
Handbook of Biometrics for Forensic Science, 221-239, 2017
132017
Validation of likelihood ratio methods for forensic evidence evaluation handling multimodal score distributions
R Haraksim, D Ramos, D Meuwly
IET biometrics 6 (2), 61-69, 2017
112017
Altered fingerprint detection–algorithm performance evaluation
R Haraksim, A Anthonioz, C Champod, M Olsen, J Ellingsgaard, ...
2016 4th International Conference on Biometrics and Forensics (IWBF), 1-6, 2016
102016
Study on fingermark and palmmark identification technologies for their implementation in the schengen information system
R Haraksim, J Galbally, L Beslay
Luxembourg: Publication office of the European Union. Doi 10, 852462, 2019
92019
Multiple AUV control in an operational context: a leader-follower approach
R Haraksim, L Brignone, J Opderbecke
OCEANS 2009-EUROPE, 1-6, 2009
92009
Fingermark quality assessment framework with classic and deep learning ensemble models
T Oblak, R Haraksim, P Peer, L Beslay
Knowledge-Based Systems 250, 109148, 2022
82022
Fingerprint quality: A lifetime story
J Galbally, R Haraksim, L Beslay
2018 International Conference of the Biometrics Special Interest Group …, 2018
72018
Assignment of the evidential value of a fingermark general pattern using a Bayesian network
R Haraksim, D Meuwly, G Doekhie, P Vergeer, M Sjerps
2013 International Conference of the BIOSIG Special Interest Group (BIOSIG …, 2013
72013
Fingermark quality assessment: An open-source toolbox
T Oblak, R Haraksim, L Beslay, P Peer
2021 International Conference of the Biometrics Special Interest Group …, 2021
62021
Performance evaluation of source camera attribution by using likelihood ratio methods
P Ferrara, R Haraksim, L Beslay
Journal of Imaging 7 (7), 116, 2021
52021
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