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pro vyhledávání: '"Rizk, A. A."'
Publikováno v:
Contacts. jul-dic2023, Vol. 75 Issue 283/284, p463-466. 4p.
Akademický článek
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Autor:
Salib, Zaki Rizk
Publikováno v:
BMJ: British Medical Journal, 2010 Jun . 340(7760), 1362-1362.
Externí odkaz:
https://www.jstor.org/stable/20734584
Autor:
Khurdula, Harsha Vardhan, Rizk, Basem, Khaitan, Indus, Anjaria, Janit, Srivastava, Aviral, Khaitan, Rajvardhan
Current benchmarks for evaluating Vision Language Models (VLMs) often fall short in thoroughly assessing model abilities to understand and process complex visual and textual content. They typically focus on simple tasks that do not require deep reaso
Externí odkaz:
http://arxiv.org/abs/2411.15201
Autor:
Lin, Spencer, Rizk, Basem, Jun, Miru, Artze, Andy, Sullivan, Caitlin, Mozgai, Sharon, Fisher, Scott
The rise in capability and ubiquity of generative artificial intelligence (AI) technologies has enabled its application to the field of Socially Interactive Agents (SIAs). Despite rising interest in modern AI-powered components used for real-time SIA
Externí odkaz:
http://arxiv.org/abs/2410.20116
Indoor localization has become increasingly important due to its wide-ranging applications in indoor navigation, emergency services, the Internet of Things (IoT), and accessibility for individuals with special needs. Traditional localization systems
Externí odkaz:
http://arxiv.org/abs/2410.02329
This paper presents a novel system for reconstructing high-resolution GPS trajectory data from truncated or synthetic low-resolution inputs, addressing the critical challenge of balancing data utility with privacy preservation in mobility application
Externí odkaz:
http://arxiv.org/abs/2410.12818
Autor:
Basu, Kinjal, Abdelaziz, Ibrahim, Bradford, Kelsey, Crouse, Maxwell, Kate, Kiran, Kumaravel, Sadhana, Goyal, Saurabh, Munawar, Asim, Rizk, Yara, Wang, Xin, Lastras, Luis, Kapanipathi, Pavan
Autonomous agent applications powered by large language models (LLMs) have recently risen to prominence as effective tools for addressing complex real-world tasks. At their core, agentic workflows rely on LLMs to plan and execute the use of tools and
Externí odkaz:
http://arxiv.org/abs/2409.03797
Locating the persons moving through an environment without the necessity of them being equipped with special devices has become vital for many applications including security, IoT, healthcare, etc. Existing device-free indoor localization systems com
Externí odkaz:
http://arxiv.org/abs/2409.00030
Accurate taxi-demand prediction is essential for optimizing taxi operations and enhancing urban transportation services. However, using customers' data in these systems raises significant privacy and security concerns. Traditional federated learning
Externí odkaz:
http://arxiv.org/abs/2408.04931