Zobrazeno 1 - 10
of 20 311
pro vyhledávání: '"Naseer, A."'
Publikováno v:
Chin. J. Phys. 91(2024)916-931
In this paper, we explore the existence of spherically symmetric strange quark configurations coupled with anisotropic fluid setup in the framework of modified Gauss-Bonnet theory. In this regard, we adopt two models such as \emph{(i)} $f(\mathcal{G}
Externí odkaz:
http://arxiv.org/abs/2411.01125
We conducted a multi-wavelength analysis of the blazar Mrk\,501, utilizing observations from \emph{Astro}Sat (SXT, LAXPC), \emph{Swift-UVOT}, and \emph{Fermi-LAT} during the period August 15, 2016 to March 27, 2022. The resulting multi-wavelength lig
Externí odkaz:
http://arxiv.org/abs/2411.00592
We conducted a comprehensive temporal and spectral study of the FSRQ PKS 0805-07 by using the broadband observations from the Fermi-LAT and Swift-XRT/UVOT instruments over the period MJD 54684-60264. The 3-day binned $\gamma$-ray light curve during t
Externí odkaz:
http://arxiv.org/abs/2410.23181
Two-dimensional ferroelectric materials are beneficial for power-efficient memory devices and transistor applications. Here, we predict out-of-plane ferroelectricity in a new family of buckled metal oxide (MO; M: Ge, Sn, Pb) monolayers with significa
Externí odkaz:
http://arxiv.org/abs/2410.19582
Autor:
Amjad, Haadia, Goeller, Kilian, Seitz, Steffen, Knoll, Carsten, Bajwa, Naseer, Tetzlaff, Ronald, Malik, Muhammad Imran
Deep learning is actively being used in biometrics to develop efficient identification and verification systems. Handwritten signatures are a common subset of biometric data for authentication purposes. Generative adversarial networks (GANs) learn fr
Externí odkaz:
http://arxiv.org/abs/2410.06041
Autor:
Sharif, M., Naseer, Tayyab
Publikováno v:
Pramana 98(2024)25
This article aims to investigate various anisotropic stellar models in the background of $f(\mathcal{R},\mathcal{T},\mathcal{Q})$ gravity, where $\mathcal{Q}=\mathcal{R}_{\varphi\vartheta}\mathcal{T}^{\varphi\vartheta}$. In this regard, we adopt two
Externí odkaz:
http://arxiv.org/abs/2410.05989
Autor:
Nawaz, Umair, Awais, Muhammad, Gani, Hanan, Naseer, Muzammal, Khan, Fahad, Khan, Salman, Anwer, Rao Muhammad
Capitalizing on vast amount of image-text data, large-scale vision-language pre-training has demonstrated remarkable zero-shot capabilities and has been utilized in several applications. However, models trained on general everyday web-crawled data of
Externí odkaz:
http://arxiv.org/abs/2410.01407
Recent attention-based volumetric segmentation (VS) methods have achieved remarkable performance in the medical domain which focuses on modeling long-range dependencies. However, for voxel-wise prediction tasks, discriminative local features are key
Externí odkaz:
http://arxiv.org/abs/2410.01003
Autor:
Noman, Mubashir, Ahsan, Noor, Naseer, Muzammal, Cholakkal, Hisham, Anwer, Rao Muhammad, Khan, Salman, Khan, Fahad Shahbaz
Large multimodal models (LMMs) have shown encouraging performance in the natural image domain using visual instruction tuning. However, these LMMs struggle to describe the content of remote sensing images for tasks such as image or region grounding,
Externí odkaz:
http://arxiv.org/abs/2409.16261
State-space models (SSMs), exemplified by S4, have introduced a novel context modeling method by integrating state-space techniques into deep learning. However, they struggle with global context modeling due to their data-independent matrices. The Ma
Externí odkaz:
http://arxiv.org/abs/2409.11867