Zobrazeno 1 - 10
of 23 960
pro vyhledávání: '"Omran IN"'
Anomalies such as redundant, inconsistent, contradictory, and deficient values in a Knowledge Graph (KG) are unavoidable, as these graphs are often curated manually, or extracted using machine learning and natural language processing techniques. Ther
Externí odkaz:
http://arxiv.org/abs/2412.04780
Autor:
Yun, Jooyeol, Abati, Davide, Omran, Mohamed, Choo, Jaegul, Habibian, Amirhossein, Wiggers, Auke
Generative models have become a powerful tool for image editing tasks, including object insertion. However, these methods often lack spatial awareness, generating objects with unrealistic locations and scales, or unintentionally altering the scene ba
Externí odkaz:
http://arxiv.org/abs/2410.13564
The proposed research aims to develop an innovative semantic query processing system that enables users to obtain comprehensive information about research works produced by Computer Science (CS) researchers at the Australian National University (ANU)
Externí odkaz:
http://arxiv.org/abs/2405.15374
Autor:
Ezzeddine, Fatima, Saad, Mirna, Ayoub, Omran, Andreoletti, Davide, Gjoreski, Martin, Sbeity, Ihab, Langheinrich, Marc, Giordano, Silvia
Anomaly detection (AD), also referred to as outlier detection, is a statistical process aimed at identifying observations within a dataset that significantly deviate from the expected pattern of the majority of the data. Such a process finds wide app
Externí odkaz:
http://arxiv.org/abs/2404.06144
Autor:
Ayoub, Omran, Andreoletti, Davide, Knapińska, Aleksandra, Goścień, Róża, Lechowicz, Piotr, Leidi, Tiziano, Giordano, Silvia, Rottondi, Cristina, Walkowiak, Krzysztof
Adapting to concept drift is a challenging task in machine learning, which is usually tackled using incremental learning techniques that periodically re-fit a learning model leveraging newly available data. A primary limitation of these techniques is
Externí odkaz:
http://arxiv.org/abs/2404.05304
Autor:
Rubegni, Elisa, Ayoub, Omran, Rizzo, Stefania Maria Rita, Barbero, Marco, Bernegger, Guenda, Faraci, Francesca, Mangili, Francesca, Soldini, Emiliano, Trimboli, Pierpaolo, Facchini, Alessandro
The widespread use of Artificial Intelligence-based tools in the healthcare sector raises many ethical and legal problems, one of the main reasons being their black-box nature and therefore the seemingly opacity and inscrutability of their characteri
Externí odkaz:
http://arxiv.org/abs/2404.04638
In recent years, there has been a notable increase in the deployment of machine learning (ML) models as services (MLaaS) across diverse production software applications. In parallel, explainable AI (XAI) continues to evolve, addressing the necessity
Externí odkaz:
http://arxiv.org/abs/2404.03348
A reconfigurable intelligent surface (RIS) is an essential component in the architecture of the next generation of wireless communication systems. An RIS is deployed to provide a controllability to the multi-path environment between the transmitter a
Externí odkaz:
http://arxiv.org/abs/2403.02526
Publikováno v:
Arab Gulf Journal of Scientific Research, 2023, Vol. 42, Issue 4, pp. 1609-1623.
Externí odkaz:
http://www.emeraldinsight.com/doi/10.1108/AGJSR-04-2023-0158
Publikováno v:
International Journal of the Cardiovascular Academy, Vol 10, Iss 4, Pp 102-114 (2024)
Background and Aim: The objective of this study was to investigate the impact of appropriate blood pressure (BP) control on left atrial (LA) function in recently diagnosed individuals with systemic hypertension (HTN), as assessed by two-dimensional (
Externí odkaz:
https://doaj.org/article/0e50cc823f77434bba36de4786e48df0