Zobrazeno 1 - 10
of 158
pro vyhledávání: '"Ali Samad"'
Autor:
Mobeen Shahroz, Muhammad Faheem Mushtaq, Rizwan Majeed, Ali Samad, Zaigham Mushtaq, Urooj Akram
Publikováno v:
IEEE Access, Vol 10, Pp 26307-26319 (2022)
The internet provides a very vast amount of sources of news and the user has to search for desirable news by spending a lot of time because the user always prefers their related interest, desirable and informative news. The clustering of the news art
Externí odkaz:
https://doaj.org/article/7c3816c27367427c94bb6133834bf2fe
Autor:
Muhammad Faheem Mushtaq, Mobeen Shahroz, Ali M. Aseere, Habib Shah, Rizwan Majeed, Danish Shehzad, Ali Samad
Publikováno v:
IEEE Access, Vol 9, Pp 113901-113916 (2021)
Brain Hemorrhage is the eruption of the brain arteries due to high blood pressure or blood clotting that could be a cause of traumatic injury or death. It is the medical emergency in which a doctor also need years of experience to immediately diagnos
Externí odkaz:
https://doaj.org/article/edd3477bf0ff4d2ea014ddf0e07a5706
Autor:
Mujtaba Husnain, Malik Muhammad Saad Missen, Shahzad Mumtaz, Dost Muhammad Khan, Mickäel Coustaty, Muhammad Muzzamil Luqman, Jean-Marc Ogier, Hizbullah Khattak, Sikandar Ali, Ali Samad
Publikováno v:
Complexity, Vol 2021 (2021)
In this paper, we make use of the 2-dimensional data obtained through t-Stochastic Neighborhood Embedding (t-SNE) when applied on high-dimensional data of Urdu handwritten characters and numerals. The instances of the dataset used for experimental wo
Externí odkaz:
https://doaj.org/article/79392714b2574f2f992636cadc10199a
Multi-access Edge Computing (MEC) can be implemented together with Open Radio Access Network (O-RAN) over commodity platforms to offer low-cost deployment and bring the services closer to end-users. In this paper, a joint O-RAN/MEC orchestration usin
Externí odkaz:
http://arxiv.org/abs/2312.16142
Diffusion models are at the vanguard of generative AI research with renowned solutions such as ImageGen by Google Brain and DALL.E 3 by OpenAI. Nevertheless, the potential merits of diffusion models for communication engineering applications are not
Externí odkaz:
http://arxiv.org/abs/2311.09349
In this paper, conditional denoising diffusion probabilistic models (DDPMs) are proposed to enhance the data transmission and reconstruction over wireless channels. The underlying mechanism of DDPM is to decompose the data generation process over the
Externí odkaz:
http://arxiv.org/abs/2310.19460
Innovative foundation models, such as GPT-4 and stable diffusion models, have made a paradigm shift in the realm of artificial intelligence (AI) towards generative AI-based systems. AI and machine learning (AI/ML) algorithms are envisioned to be perv
Externí odkaz:
http://arxiv.org/abs/2310.07312
With the incredible results achieved from generative pre-trained transformers (GPT) and diffusion models, generative AI (GenAI) is envisioned to yield remarkable breakthroughs in various industrial and academic domains. In this paper, we utilize deno
Externí odkaz:
http://arxiv.org/abs/2309.08688
Generative AI has received significant attention among a spectrum of diverse industrial and academic domains, thanks to the magnificent results achieved from deep generative models such as generative pre-trained transformers (GPT) and diffusion model
Externí odkaz:
http://arxiv.org/abs/2309.08568
Wireless networks are inherently graph-structured, which can be utilized in graph representation learning to solve complex wireless network optimization problems. In graph representation learning, feature vectors for each entity in the network are ca
Externí odkaz:
http://arxiv.org/abs/2212.01904