Search results
Results: 84
Number of items: 84
-
Geradts, Z., & Nikkel, B. (2021). Change and diversity. Forensic Science International: Digital Investigation, 37, Article 301206. https://doi.org/10.1016/j.fsidi.2021.301206 -
Pločo, A., Macarulla Rodríguez, A., & Geradts, Z. (2020). Spatial-Temporal Omni-Scale Feature Learning for Person Re-Identification. In IWBF 2020 : 2020 8th International Workshop on Biometrics and Forensics (IWBF) : proceedings : Porto, Portugal, April 29-30, 2020 (pp. 121-125). IEEE. https://doi.org/10.1109/IWBF49977.2020.9107966
-
Geradts, Z. J. (2020). Crossing Borders: Forensic Science and the Fourth Industrial Revolution. Journal of Forensic Sciences, 65(1), 6-7. https://doi.org/10.1111/1556-4029.14236
-
Geradts, Z. J. (2020). The Application of Artificial Intelligence (AI) in Digital Forensic Science. Proceedings of the American Academy of Forensic Sciences, 26, 463. Article C17. https://aafs.org/common/Uploaded%20files/Resources/Proceedings/2020_Proceedings.pdf
-
Venema, A. E., & Geradts, Z. J. (2020). Digital Forensics, Deepfakes and the Legal Process. SciTech Lawyer, 16(4), 14-17, 23. https://www.americanbar.org/groups/science_technology/publications/scitech_lawyer/2020/summer/digital-forensics-deepfakes-and-legal-process/
-
Macarulla Rodriguez, A., Geradts, Z., & Worring, M. (2020). Likelihood Ratios for Deep Neural Networks in Face Comparison. Journal of Forensic Sciences, 65(4), 1169-1183. https://doi.org/10.1111/1556-4029.14324
-
Geradts, Z., Filius, N., & Ruifrok, A. (2020). Interpol review of imaging and video 2016-2019. Forensic Science International: Synergy, 2, 540-562. https://doi.org/10.1016/j.fsisyn.2020.01.017
-
Bas Seyyar, M., & Geradts, Z. J. M. H. (2020). Privacy impact assessment in large-scale digital forensic investigations. Forensic Science International: Digital Investigation, 33, Article 200906. https://doi.org/10.1016/j.fsidi.2020.200906
-
Casey, E., Geradts, Z., & Nikkel, B. (2019). Panoramic perspective of Digital Investigation. Digital Investigation, 30, 173. https://doi.org/10.1016/j.diin.2019.100886
-
Ibrahimi, S., van Noord, N., Geradts, Z., & Worring, M. (2019). Deep Metric Learning for Cross-Domain Fashion Instance Retrieval. In 2019 International Conference on Computer Vision, Workshops: proceedings : 27 October-2 November 2019, Seoul, Korea (pp. 3165-3168). IEEE Computer Society. https://doi.org/10.1109/ICCVW.2019.00390
Page 5 of 9