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Maza-Quiroga, R, Thurnhofer-Hemsi, K, López-Rodríguez, D and López-Rubio, E (2023). Regression of the Rician Noise Level in 3D Magnetic Resonance Images from the Distribution of the First Significant Digit . Axioms 12, pp. 1117 .

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

Al-Bandawi, H and Deng, G (2019). Classification of image distortion based on the generalized Benford’s law. Multimedia Tools and Applications, pp. 1-18. DOI:10.1007/s11042-019-7668-3. View Complete Reference Online information Works that this work references Works that reference this work
Azevedo, CdS, Gonçalves, RF, Gava, VL and Spinola, MdM (2021). A Benford’s Law based methodology for fraud detection in social welfare programs: Bolsa Familia analysis. Physica A 567, p. 125626. DOI:10.1016/j.physa.2020.125626. View Complete Reference Online information Works that this work references 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
Eckhartt, GM and Ruxton, GD (2023). Investigating and preventing scientific misconduct using Benford’s Law. Research Integrity and Peer Review 8(1). DOI:10.1186/s41073-022-00126-w. View Complete Reference Online information Works that this work references Works that reference this work
Hill, TP (1995). A Statistical Derivation of the Significant-Digit Law. Statistical Science 10(4), pp. 354-363. ISSN/ISBN:0883-4237. View Complete Reference Online information Works that this work references Works that reference this work
Jolion, JM (2001). Images and Benford's Law. Journal of Mathematical Imaging and Vision 14(1), pp. 73-81. ISSN/ISBN:0924-9907. DOI:10.1023/A:1008363415314. View Complete Reference Online information Works that this work references Works that reference this work
Marcel, M (2017). Benford_py: a Python Implementation of Benford's Law Tests. GitHub repository; last accessed October 8, 2021. View Complete Reference Online information Works that this work references Works that reference this work
Maza-Quiroga, R, Thurnhofer-Hemsi, K, Lopez-Rodrıguez, D and Lopez-Rubio, E (2021). Rician Noise Estimation for 3D Magnetic Resonance Images Based on Benford’s Law. In: de Bruijne M. et al. (eds) Medical Image Computing and Computer Assisted Intervention – MICCAI 2021. MICCAI 2021. Lecture Notes in Computer Science, vol 12906. Springer, Cham.. DOI:10.1007/978-3-030-87231-1_33. View Complete Reference Online information Works that this work references Works that reference this work
Milani, S, Tagliasacchi, M and Tubaro, S (2014). Discriminating multiple JPEG compressions using first digit features. APSIPA Transactions on Signal and Information Processing 3, e19. DOI:10.1017/ATSIP.2014.19. View Complete Reference Online information Works that this work references Works that reference this work
Miller, SJ (ed.) (2015). Benford's Law: Theory and Applications. Princeton University Press: Princeton and Oxford. ISSN/ISBN:978-0-691-14761-1. View Complete Reference Online information Works that this work references Works that reference this work
Pasquini, C, Boato, G and Pérez-González, F (2017). Statistical Detection of JPEG Traces in Digital Images in Uncompressed Formats. IEEE Transactions on Information Forensics and Security 12(12), pp. 2890-2905. DOI:10.1109/TIFS.2017.2725201. View Complete Reference Online information Works that this work references Works that reference this work
Sanches, J and Marques, JS (2006). Image reconstruction using the Benford law. Proceedings of the IEEE International Conference on Image Processing, Atlanta, GA, October 2006, pp. 2029-2032. ISSN/ISBN:1522-4880. DOI:10.1109/ICIP.2006.312845. 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
Smith, SW (1997). Explaining Benford's Law. Chapter 34 in: The Scientist and Engineer's Guide to Digital Signal Processing. California Technical Publishing: San Diego, CA. Republished in softcover by Newnes, 2002. ISSN/ISBN:0-9660176-3-3. View Complete Reference Online information No Bibliography works referenced by this work. Works that reference this work
Varga, D (2021). Analysis of Benford’s Law for No-Reference Quality Assessment of Natural, Screen-Content, and Synthetic Images . Electronics 10(19), p. 2378. DOI:10.3390/electronics10192378. View Complete Reference Online information Works that this work references Works that reference this work