research
∙
12/14/2022
Mathematical model of printing-imaging channel for blind detection of fake copy detection patterns
Nowadays, copy detection patterns (CDP) appear as a very promising anti-...
share
research
∙
10/28/2022
Digital twins of physical printing-imaging channel
In this paper, we address the problem of modeling a printing-imaging cha...
research
∙
10/11/2022
Printing variability of copy detection patterns
Copy detection pattern (CDP) is a novel solution for products' protectio...
research
∙
09/29/2022
Anomaly localization for copy detection patterns through print estimations
Copy detection patterns (CDP) are recent technologies for protecting pro...
research
∙
06/23/2022
Authentication of Copy Detection Patterns under Machine Learning Attacks: A Supervised Approach
Copy detection patterns (CDP) are an attractive technology that allows m...
research
∙
03/04/2022
Mobile authentication of copy detection patterns
In the recent years, the copy detection patterns (CDP) attracted a lot o...
research
∙
10/05/2021
Machine learning attack on copy detection patterns: are 1x1 patterns cloneable?
Nowadays, the modern economy critically requires reliable yet cheap prot...
research
∙
10/05/2021
Mobile authentication of copy detection patterns: how critical is to know fakes?
Protection of physical objects against counterfeiting is an important ta...
research
∙
08/31/2021
ScatSimCLR: self-supervised contrastive learning with pretext task regularization for small-scale datasets
In this paper, we consider a problem of self-supervised learning for sma...
research
∙
12/02/2019
Information bottleneck through variational glasses
Information bottleneck (IB) principle [1] has become an important elemen...
research
∙
05/14/2019
Robustification of deep net classifiers by key based diversified aggregation with pre-filtering
In this paper, we address a problem of machine learning system vulnerabi...
research
∙
05/08/2019
Reconstruction of Privacy-Sensitive Data from Protected Templates
In this paper, we address the problem of data reconstruction from privac...
research
∙
04/01/2019
Defending against adversarial attacks by randomized diversification
The vulnerability of machine learning systems to adversarial attacks que...
research
∙
03/18/2019
Clonability of anti-counterfeiting printable graphical codes: a machine learning approach
In recent years, printable graphical codes have attracted a lot of atten...
research
∙
09/10/2018
Classification by Re-generation: Towards Classification Based on Variational Inference
As Deep Neural Networks (DNNs) are considered the state-of-the-art in ma...
research
∙
09/05/2018
Bridging machine learning and cryptography in defence against adversarial attacks
In the last decade, deep learning algorithms have become very popular th...
research
∙
09/29/2017
