Zobrazeno 1 - 10
of 1 783
pro vyhledávání: '"Memmi, A."'
Autor:
Memmi, Gerard
This article focuses on comparing the notions of home spaces and invariants, in Transition Systems and more particularly, in Petri Nets as well as a variety of derived Petri Nets. After recalling basic notions of Petri Nets and semiflows, we then dis
Externí odkaz:
http://arxiv.org/abs/2403.11779
Autor:
Benjamin Memmi, Juliette Knoeri, Loïc Leveziel, Cristina Georgeon, Nacim Bouheraoua, Vincent Borderie
Publikováno v:
Scientific Reports, Vol 14, Iss 1, Pp 1-9 (2024)
Abstract Refractive error is becoming a significant public health issue. Photorefractive Keratectomy (PRK) is a corneal surface surgical technique that removes the corneal epithelium before stromal photoablation by ultraviolet radiation from the Exci
Externí odkaz:
https://doaj.org/article/6ca65e7962c94ed282fd392e9e7a8f04
Autor:
Memmi, Gerard
This lecture note focuses on comparing the notions of invariance and home spaces in Transition Systems and more particularly, in Petri Nets. We also describe how linear algebra relates to these basic notions in Computer Science, how it can be used fo
Externí odkaz:
http://arxiv.org/abs/2306.07623
Autor:
Memmi, Gerard
In this short note, we are interested in discussing characteristics of finite generating sets for $\mathcal{F}$, the set of all semiflows with non negative coefficients of a Petri Net. By systematically positioning these results over semi rings such
Externí odkaz:
http://arxiv.org/abs/2211.10405
Autor:
Memmi, Benjamin1 (AUTHOR), Knoeri, Juliette1 (AUTHOR), Leveziel, Loïc1 (AUTHOR), Georgeon, Cristina1 (AUTHOR), Bouheraoua, Nacim1 (AUTHOR), Borderie, Vincent1,2 (AUTHOR) vincent.borderie@upmc.fr
Publikováno v:
Scientific Reports. 9/7/2024, Vol. 14 Issue 1, p1-9. 9p.
Publikováno v:
Digital Communications and Networks, Vol 10, Iss 1, Pp 158-167 (2024)
The proliferation of internet communication channels has increased telecom fraud, causing billions of euros in losses for customers and the industry each year. Fraudsters constantly find new ways to engage in illegal activity on the network. To reduc
Externí odkaz:
https://doaj.org/article/8e33b03e1c4d452dba28c6d330e2b350
Publikováno v:
In Digital Communications and Networks February 2024 10(1):158-167
Deep Neural Networks (DNNs) in Computer Vision (CV) are well-known to be vulnerable to Adversarial Examples (AEs), namely imperceptible perturbations added maliciously to cause wrong classification results. Such variability has been a potential risk
Externí odkaz:
http://arxiv.org/abs/2007.15290
Deep Neural Networks (DNNs) are well-known to be vulnerable to Adversarial Examples (AEs). A large amount of efforts have been spent to launch and heat the arms race between the attackers and defenders. Recently, advanced gradient-based attack techni
Externí odkaz:
http://arxiv.org/abs/2005.13712
This is the report for the PRIM project in Telecom Paris. This report is about applications based on spatial-frequency transform and deep learning techniques. In this report, there are two main works. The first work is about the enhanced JPEG compres
Externí odkaz:
http://arxiv.org/abs/2004.02756