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pro vyhledávání: '"Marwan ."'
Deep Neural Network (DNN) based classifiers have recently been used for the modulation classification of RF signals. These classifiers have shown impressive performance gains relative to conventional methods, however, they are vulnerable to impercept
Externí odkaz:
http://arxiv.org/abs/2410.06339
Autor:
Chammouma, Marwan, Jouanlanne, Manon, Egelé, Antoine, Favier, Damien, Farago, Jean, Hourlier-Fargette, Aurélie
Spontaneous mechanical self-assembly of monodisperse bubbles generally leads to disordered foams at low density: producing crystalline structures such as Kelvin foams has proven to be challenging experimentally, despite them being a minimum of energy
Externí odkaz:
http://arxiv.org/abs/2409.20114
Deep reinforcement learning has seen successful implementations on humanoid robots to achieve dynamic walking. However, these implementations have been so far successful in simple environments void of obstacles. In this paper, we aim to achieve biped
Externí odkaz:
http://arxiv.org/abs/2410.08212
Autor:
Marwan, Norbert
Publikováno v:
Frontiers in Applied Mathematics and Statistics, 9, 1129105 (2023)
The analysis of event time series is in general challenging. Most time series analysis tools are limited for the analysis of this kind of data. Recurrence analysis, a powerful concept from nonlinear time series analysis, provides several opportunitie
Externí odkaz:
http://arxiv.org/abs/2409.08398
The rising use of Large Language Models (LLMs) to create and disseminate malware poses a significant cybersecurity challenge due to their ability to generate and distribute attacks with ease. A single prompt can initiate a wide array of malicious act
Externí odkaz:
http://arxiv.org/abs/2409.07587
In scientific research, charts are usually the primary method for visually representing data. However, the accessibility of charts remains a significant concern. In an effort to improve chart understanding pipelines, we focus on optimizing the chart
Externí odkaz:
http://arxiv.org/abs/2409.04683
Autor:
Marwan, Norbert, Kraemer, K. Hauke
Publikováno v:
European Physical Journal -- Special Topics, 232, 5--27 (2023)
The last decade has witnessed a number of important and exciting developments that had been achieved for improving recurrence plot based data analysis and to widen its application potential. We will give a brief overview about important and innovativ
Externí odkaz:
http://arxiv.org/abs/2409.04110
Autor:
Osman, Nada, Torki, Marwan
Anomaly action detection and localization play an essential role in security and advanced surveillance systems. However, due to the tremendous amount of surveillance videos, most of the available data for the task is unlabeled or semi-labeled with th
Externí odkaz:
http://arxiv.org/abs/2408.13643
Autor:
Besrour, Marwan, Lavoie, Jacob, Omrani, Takwa, Martin-Hardy, Gabriel, Koleibi, Esmaeil Ranjbar, Menard, Jeremy, Koua, Konin, Marcoux, Philippe, Boukadoum, Mounir, Fontaine, Rejean
The computational complexity of deep learning algorithms has given rise to significant speed and memory challenges for the execution hardware. In energy-limited portable devices, highly efficient processing platforms are indispensable for reproducing
Externí odkaz:
http://arxiv.org/abs/2408.07734
Autor:
Omar, Marwan
In recent years, the convergence of cybersecurity, artificial intelligence (AI), and data management has emerged as a critical area of research, driven by the increasing complexity and interdependence of modern technological ecosystems. This paper pr
Externí odkaz:
http://arxiv.org/abs/2408.05888