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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.

This work cites the following items of the Benford Online Bibliography:

Benford, F (1938). The law of anomalous numbers. Proceedings of the American Philosophical Society, Vol. 78, No. 4 (Mar. 31, 1938), pp. 551-572. View Complete Reference Online information No Bibliography works referenced by this work. Works that reference this work
Bonettini, N, Bestagini, P, Milani, S and Tubaro, S (2020). On the use of Benford's law to detect GAN-generated images. Preprint arXiv:arXiv:2004.07682 [cs.CV]; last accessed April 21, 2020 (2020 25th International Conference on Pattern Recognition (ICPR), pp. 5495-5502) . View Complete Reference Online information Works that this work references Works that reference this work
Del Acebo, E and Sbert, M (2005). Benford's Law for Natural and Synthetic Images. Proc. of the First Workshop on Computational Aesthetics in Graphics, Visualization and Imaging, L. Neumann, M. Sbert, B. Gooch, and W. Purgathofer, Eds., Girona, Spain, May 2005, pp. 169–176. ISSN/ISBN:1816-0859. DOI:10.2312/COMPAESTH/COMPAESTH05/169-176. View Complete Reference Online information Works that this work references Works that reference this work
Fu, D, Shi, YQ and Su, W (2007). A generalized Benford’s law for JPEG coefficients and its applications in image forensics. Proceedings of SPIE, Volume 6505, Security, Steganography and Watermarking of Multimedia Contents IX, San Jose, California, January 28 - February 1, 2007, pp. 65051L-65051L-11. DOI:10.1117/12.704723. View Complete Reference Online information Works that this work references Works that reference this work
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). DOI:10.1117/12.2077531. View Complete Reference Online information Works that this work references Works that reference this work
Hill, TP (1998). The First-Digit Phenomenon. American Scientist 86 (4), pp. 358-363. ISSN/ISBN:0003-0996. DOI:10.1511/1998.4.358. View Complete Reference Online information Works that this work references Works that reference this work
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. View Complete Reference Online information Works that this work references Works that reference this work
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. View Complete Reference Online information Works that this work references Works that reference this work
Iorliam, A and Shangbum, FC (2017). On the Use of Benford’s Law to Detect JPEG Biometric Data Tampering. Journal of Information Security 8, pp. 240-256. DOI:10.4236/jis.2017.83016. View Complete Reference Online information Works that this work references Works that reference this work
Li, XH, Zhao, YQ, Liao, M, Shih, FY and Shi, YQ (2012). Detection of tampered region for JPEG images by using mode-based first digit features. EURASIP Journal on Advances in Signal Processing, 2012:190. DOI:10.1186/1687-6180-2012-190. View Complete Reference Online information Works that this work references Works that reference this work
Satapathy, G, Bhattacharya, G, Puhan, NB and Ho, ATS (2020). Generalized Benford’s Law for Fake Fingerprint Detection. Proceedings of 2020 IEEE Applied Signal Processing Conference (ASPCON), Kolkata, pp. 242-246. DOI:10.1109/ASPCON49795.2020.9276660. View Complete Reference Online information Works that this work references Works that reference this work