Cross Reference Up

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.

This work is cited by the following items of the Benford Online Bibliography:

Note that this list may be incomplete, and is currently being updated. Please check again at a later date.

Amerini, I, Becarelli, R, Caldelli, R, Del Mastio, A and (2014). Splicing forgeries localization through the use of first digit features. Proceedings of 2014 IEEE International Workshop on Information Forensics and Security (WIFS), Atlanta, GA, USA, 2014, pp. 143-148 . DOI:10.1109/WIFS.2014.7084318. View Complete Reference Online information Works that this work references Works that reference this work
Amruthnath, N (2020). Benford’s Law: Applying to Existing Data. Posted on R-bloggers.com, last accessed August 29, 2020. View Complete Reference Online information Works that this work references No Bibliography works reference this work
Barbancho, I, Tardón, LJ, Barbancho, AM and Sbert, M (2016). Benford's Law for Music Analysis. Proceedings of the 16th ISMIR Conference, Malaga, Spain, pp. 735-741. View Complete Reference Online information Works that this work references Works that reference this work
Berger, A and Hill, TP (2015). An Introduction to Benford's Law. Princeton University Press: Princeton, NJ. ISSN/ISBN:9780691163062. 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
den Heijer, E and Eiben, AE (2014). Investigating aesthetic measures for unsupervised evolutionary art. Swarm and Evolutionary Computation, Vol. 16, pp. 52–68. DOI:10.1016/j.swevo.2014.01.002. View Complete Reference Online information Works that this work references Works that reference this work
Fernandes, P and Antunes, M (2023). Benford’s law applied to digital forensic analysis. Forensic Science International: Digital Investigation 45, p. 301515. DOI:10.1016/J.FSIDI.2023.301515. 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
Giles, DE (2013). Exact Asymptotic Goodness-of-Fit Testing for Discrete Circular Data, With Applications. Chilean Journal of Statistics 4(1), pp.19-34. ISSN/ISBN:0718-7912. View Complete Reference Online information Works that this work references No Bibliography works reference this work
Grabowski, F and Trojanowski, P (2006). Benford's law in image analysis. Proceedings of the 1st Conference on Tools of Information Technology, Rzeszów, Poland, 15 September 2006, pp. 72-78. View Complete Reference Online information Works that this work references No Bibliography works reference this work
Iorliam, A (2016). Application of power laws to biometrics, forensics and network traffic analysis. PhD Thesis, University of Surrey. View Complete Reference Online information Works that this work references Works that reference this work
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. View Complete Reference Online information Works that this work references No Bibliography works 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, Poh, N and Shi, YQ (2014). Do Biometric Images Follow Benford's Law?. Proceedings of the 22nd European Signal Processing Conf.(Eusipco). DOI:10.1109/IWBF.2014.6914261. 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, Tirunagari, S, Ho, ATS, Li, S, Waller, A and Poh, N (2017). "Flow Size Difference" Can Make a Difference: Detecting Malicious TCP Network Flows Based on Benford's Law. arXiv:1609.04214v2 [cs.CR], last accessed February 6, 2017. View Complete Reference Online information Works that this work references Works that reference this work
Li, B, Shi, YQ and Huang, J (2008). Detecting doubly compressed JPEG images by using mode based first digit features. Proceedings of 2008 IEEE 10th Workshop on Multimedia Signal Processing, pp. 730–735. DOI:10.1109/MMSP.2008.4665171. View Complete Reference Online information Works that this work references Works that reference this work
Mainusch, NM (2020). On Benford's law - Computing a Bayes factor with the Savage-Dickey method to quantify conformance of numerical data to Benford's law. Bachelor's Thesis, University of Osnabrueck, Institute of Cognitive Science, Germany. View Complete Reference Online information Works that this work references No Bibliography works 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
Moin, SS and Islam, S (2017). Benford's law for detecting contrast enhancement. Proceedings of 2017 Fourth International Conference on Image Information Processing (ICIIP), Dec 21-23, pp. 1-4. DOI:10.1109/ICIIP.2017.8313717. View Complete Reference Online information Works that this work references Works that reference this work
O'Mahony, L, O'Sullivan, DJP and Nikolov, NS (2023). On the Detection of Anomalous or Out-of-Distribution Data in Vision Models Using Statistical Techniques.. In: Proceedings of the 3rd International Conference on Artificial Intelligence and Computer Vision (AICV2023), March 5–7, 2023. AICV 2023. Lecture Notes on Data Engineering and Communications Technologies, vol 164. Springer, Cham.. DOI:10.1007/978-3-031-27762-7_40. View Complete Reference Online information Works that this work references No Bibliography works reference this work
Perez-Gonzalez, F, Heileman, GL and Abdallah, CT (2007). Benford's Law in Image Processing. Image Processing, pp I-405 - I-408. ICIP 2007. IEEE International Conference. ISSN/ISBN:1522-4880. DOI:10.1109/ICIP.2007.4378977. View Complete Reference Online information Works that this work references Works that reference this work
Pinchas, M (2016). Inspection of the Output of a Convolution and Deconvolution Process from the Leading Digit Point of View—Benford’s Law. Journal of Signal and Information Processing 7, pp. 227-251. DOI:10.4236/jsip.2016.74020. View Complete Reference Online information Works that this work references No Bibliography works reference this work
Qadir, G, Zhao, X and Ho, ATS (2010). Estimating JPEG2000 Compression for Image Forensics Using the Benford’s Law. Proc. of SPIE Vol. 7723, pp. 77230J1 -77230J10. DOI:10.1117/12.855085. View Complete Reference Online information Works that this work references Works that reference this work
Qadir, G, Zhao, X, Ho, ATS and Casey, M (2011). Image forensic of glare feature for improving image retrieval using Benford's Law. Proceedings of 2011 IEEE International Symposium on Circuits and Systems (ISCAS), pp. 2661--2664. ISSN/ISBN:0271-4302. DOI:10.1109/ISCAS.2011.5938152. View Complete Reference Online information Works that this work references Works that reference this work
Sahu, SK, Java, A and Shaikh, A (2021). On The Connection of Benford’s Law and Neural Networks. Preprint arXiv:2102.03313 [cs.LG]; last accessed February 21, 2021. View Complete Reference Online information Works that this work references No Bibliography works reference this work
Sahu, SK, Java, A and Shaikh, A (2021). Rethinking Neural Networks with Benford’s Law. Proceedings of Fourth Workshop on Machine Learning and the Physical Sciences (NeurIPS 2021). 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
Sun, L, Ho, ATS, Xia, Z, Chen, J, Huang, X and Zhang, Y (2017). Detection and Classification of Malicious Patterns In Network Traffic Using Benford’s Law. 2017 Asia-Pacific Signal and Information Processing Association Annual Summit and Conference (APSIPA ASC), Kuala Lumpur, pp. 864-872. DOI:10.1109/APSIPA.2017.8282154. View Complete Reference Online information Works that this work references Works that reference this work
Tariq, J and Ijaz, A (2020). HEVC Intra Mode Selection Using Benford’s Law. Circuits, Systems, and Signal Processing. DOI:10.1007/s00034-020-01482-y. View Complete Reference Online information Works that this work references No Bibliography works reference this work
Tong, SF, Zhang, Z, Xie, Y and Wu, X (2013). Image Splicing Detection Based on Statistical Properties of Benford Model. Proceedings of the 2nd International Conference on Computer Science and Electronics Engineering (ICCSEE 2013), pp. 0792-0795. ISSN/ISBN:978-90-78677-61-1. DOI:10.2991/iccsee.2013.200. View Complete Reference Online information Works that this work references Works that reference this work
Vishnu, U (2021). Deepfake Detection using Benford’s Law and Distribution Variance Statistic. International Research Journal of Engineering and Technology(IRJET) 08(10), pp. 712-719. View Complete Reference Online information Works that this work references No Bibliography works reference this work
Wang, J, Cha, B-H, Cho, S-H and Kuo, C-CJ (2009). Understanding Benford’s Law and its Vulnerability in Image Forensics. IEEE International Conference on Multimedia and Expo, ICME 2009, pp. 1568 - 1571. ISSN/ISBN:1945-7871. DOI:10.1109/ICME.2009.5202811. View Complete Reference Online information Works that this work references Works that reference this work
Xu, B, Wang, J, Liu, G and Dai, Y (2011). Photorealistic computer graphics forensics based on leading digit law. Journal of Electronics (China) 28(1) pp. 95-100. DOI:10.1007/s11767-011-0474-3. View Complete Reference Online information Works that this work references Works that reference this work
Zaharis, A, Martini, A, Tryfonas, T, Ilioudis, C and Pangalos, G (2011). Lightweight Steganalysis Based on Image Reconstruction and Lead Digit Distribution Analysis. nternational Journal of Digital Crime and Forensics 3(4), pp. 29-41. DOI:10.4018/jdcf.2011100103. View Complete Reference Online information Works that this work references Works that reference this work