Zobrazeno 1 - 10
of 102
pro vyhledávání: '"Taran, Olga"'
Hand pose estimation from egocentric video has broad implications across various domains, including human-computer interaction, assistive technologies, activity recognition, and robotics, making it a topic of significant research interest. The effica
Externí odkaz:
http://arxiv.org/abs/2409.07337
Autor:
Lastufka, Erica, Bait, Omkar, Taran, Olga, Drozdova, Mariia, Kinakh, Vitaliy, Piras, Davide, Audard, Marc, Dessauges-Zavadsky, Miroslava, Holotyak, Taras, Schaerer, Daniel, Voloshynovskiy, Svyatoslav
Publikováno v:
A&A 690, A310 (2024)
Self-supervised learning (SSL) applied to natural images has demonstrated a remarkable ability to learn meaningful, low-dimension representations without labels, resulting in models that are adaptable to many different tasks. Until now, applications
Externí odkaz:
http://arxiv.org/abs/2408.06147
Autor:
Drozdova, Mariia, Kinakh, Vitaliy, Bait, Omkar, Taran, Olga, Lastufka, Erica, Dessauges-Zavadsky, Miroslava, Holotyak, Taras, Schaerer, Daniel, Voloshynovskiy, Slava
Reconstructing sky models from dirty radio images for accurate source localization and flux estimation is crucial for studying galaxy evolution at high redshift, especially in deep fields using instruments like the Atacama Large Millimetre Array (ALM
Externí odkaz:
http://arxiv.org/abs/2402.10204
Copy detection patterns (CDP) present an efficient technique for product protection against counterfeiting. However, the complexity of studying CDP production variability often results in time-consuming and costly procedures, limiting CDP scalability
Externí odkaz:
http://arxiv.org/abs/2309.16866
Autor:
Tutt, Joakim, Taran, Olga, Chaban, Roman, Pulfer, Brian, Belousov, Yury, Holotyak, Taras, Voloshynovskiy, Slava
Nowadays, copy detection patterns (CDP) appear as a very promising anti-counterfeiting technology for physical object protection. However, the advent of deep learning as a powerful attacking tool has shown that the general authentication schemes are
Externí odkaz:
http://arxiv.org/abs/2212.07326
Autor:
Belousov, Yury, Pulfer, Brian, Chaban, Roman, Tutt, Joakim, Taran, Olga, Holotyak, Taras, Voloshynovskiy, Slava
In this paper, we address the problem of modeling a printing-imaging channel built on a machine learning approach a.k.a. digital twin for anti-counterfeiting applications based on copy detection patterns (CDP). The digital twin is formulated on an in
Externí odkaz:
http://arxiv.org/abs/2210.17420
Autor:
Chaban, Roman, Taran, Olga, Tutt, Joakim, Belousov, Yury, Pulfer, Brian, Holotyak, Taras, Voloshynovskiy, Slava
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 industry due to its numerous benefits in comparison to alternative prot
Externí odkaz:
http://arxiv.org/abs/2210.05343
Autor:
Pulfer, Brian, Belousov, Yury, Tutt, Joakim, Chaban, Roman, Taran, Olga, Holotyak, Taras, Voloshynovskiy, Slava
Copy detection patterns (CDP) are recent technologies for protecting products from counterfeiting. However, in contrast to traditional copy fakes, deep learning-based fakes have shown to be hardly distinguishable from originals by traditional authent
Externí odkaz:
http://arxiv.org/abs/2209.15625
Autor:
Pulfer, Brian, Chaban, Roman, Belousov, Yury, Tutt, Joakim, Taran, Olga, Holotyak, Taras, Voloshynovskiy, Slava
Copy detection patterns (CDP) are an attractive technology that allows manufacturers to defend their products against counterfeiting. The main assumption behind the protection mechanism of CDP is that these codes printed with the smallest symbol size
Externí odkaz:
http://arxiv.org/abs/2206.11793
Autor:
Taran, Olga, Tutt, Joakim, Holotyak, Taras, Chaban, Roman, Bonev, Slavi, Voloshynovskiy, Slava
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 of things and brand protection applications. However, the security of C
Externí odkaz:
http://arxiv.org/abs/2203.02397