Hildebrandt, M and Dittmann, J (2015). Benford’s Law based detection of latent fingerprint forgeries on the example of artificial sweat printed fingerprints captured by confocal laser scanning microscopes. In: Proceedings SPIE 9409, Media Watermarking, Security, and Forensics 94090A (4 March 2015).
This work is cited by the following items of the Benford Online Bibliography:
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Iorliam, A (2016). Application of power laws to biometrics, forensics and network traffic analysis. PhD Thesis, University of Surrey.
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Iorliam, A, Emmanual, O and Shehu, YI (2021). An Investigation of "Benford's" Law Divergence and Machine Learning Techniques for "Intra-Class" Separability of Fingerprint Images. Preprint arXiv:2201.01699 [cs.CV]; last accessed January 12, 2022.
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Iorliam, A, Ho, AT, Poh, N, Zhao, X and Xia, Z (2017). Benford's law for classification of biometric images. In: User-Centric Privacy and Security in Biometrics, Claus Vielhauer (Ed.). ISSN/ISBN:9781785612077. DOI:10.1049/PBSE004E_ch11.
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Iorliam, A, Ho, ATS, Waller, A and Zhao, X (2017). Using Benford's Law Divergence and Neural Networks for Classification and Source Identification of Biometric Images. In: Shi Y., Kim H., Perez-Gonzalez F., Liu F. (eds) Digital Forensics and Watermarking. IWDW 2016. Lecture Notes in Computer Science, vol 10082. Springer, Cham, pp. 88-105. DOI:10.1007/978-3-319-53465-7_7.
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