DETECTION OF PRINTED FALSE ATTACKS USING NEURAL NETWORKS
This article discusses a method for detecting false positives against a biometric facial recognition system based on deep convolutional neural networks. The proposed method is designed to detect printed false positives and is tested on open databases of real and fake faces, and the results are analyzed. The types of false positive attacks launched against a biometric system based on existing faces are analyzed.
Institutions
- Kurgan State University (RU)
Publication Details
- Journal
- Zenodo (CERN European Organization for Nuclear Research)
- Published
- 2025-10-03
- DOI
- https://doi.org/10.5281/zenodo.17258688
- Primary Topic
- Milk Quality and Mastitis in Dairy Cows
- Type
- article
- Field-Weighted Citation Impact
- 0.00