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20172024
most citedInformation bottleneck through variational glasses

23 citations · 39 across the 14 of their papers we have counts for

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Showing cs.CRShow all

7 papers · 1 filter

cs.CR2022

Printing variability of copy detection patterns

Roman Chaban, Olga Taran, Joakim Tutt +4

Copy detection pattern (CDP) is a novel solution for products' protection against counterfeiting, which gains its popularity in recent years. CDP attracts the anti-counterfeiting i…

cs.CR20221 cited

Mobile authentication of copy detection patterns

Olga Taran, Joakim Tutt, Taras Holotyak +3

In the recent years, the copy detection patterns (CDP) attracted a lot of attention as a link between the physical and digital worlds, which is of great interest for the internet o…

cs.CR20213 cited

Machine learning attack on copy detection patterns: are 1x1 patterns cloneable?

Roman Chaban, Olga Taran, Joakim Tutt +3

Nowadays, the modern economy critically requires reliable yet cheap protection solutions against product counterfeiting for the mass market. Copy detection patterns (CDP) are consi…

cs.CR2021

Mobile authentication of copy detection patterns: how critical is to know fakes?

Olga Taran, Joakim Tutt, Taras Holotyak +3

Protection of physical objects against counterfeiting is an important task for the modern economies. In recent years, the high-quality counterfeits appear to be closer to originals…

cs.CR2019

Clonability of anti-counterfeiting printable graphical codes: a machine learning approach

Olga Taran, Slavi Bonev, Slava Voloshynovskiy

In recent years, printable graphical codes have attracted a lot of attention enabling a link between the physical and digital worlds, which is of great interest for the IoT and bra…

cs.CR2018

Bridging machine learning and cryptography in defence against adversarial attacks

Olga Taran, Shideh Rezaeifar, Slava Voloshynovskiy

In the last decade, deep learning algorithms have become very popular thanks to the achieved performance in many machine learning and computer vision tasks. However, most of the de…