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pro vyhledávání: '"Awais Muhammad"'
Publikováno v:
Nonlinear Engineering, Vol 13, Iss 1, Pp 485-92 (2024)
We investigate a class of third-order nonlinear integro-differential equations (IDEs) with parallel computing of intelligent Internet of Things and wireless networks for numerical solutions. A numerical scheme based on the Haar wavelet has been estab
Externí odkaz:
https://doaj.org/article/fb378e705f5f40d4ac2eaa9738f84d07
Autor:
Wubin Xie, Malay Kanti Mridha, Anaya Gupta, Dian Kusuma, Awais Muhammad Butt, Mehedi Hasan, Soren Brage, Marie Loh, Khadija Irfan Khawaja, Rajendra Pradeepa, Vinita Jha, Anuradhani Kasturiratne, Prasad Katulanda, Ranjit Mohan Anjana, John C Chambers
Publikováno v:
BMC Public Health, Vol 23, Iss 1, Pp 1-10 (2023)
Abstract Introduction Tobacco use, in both smoking and smokeless forms, is highly prevalent among South Asian adults. The aims of the study were twofold: (1) describe patterns of SLT and combustible tobacco product use in four South Asian countries s
Externí odkaz:
https://doaj.org/article/bc2a32d83a594d149557efc7661c34cd
Publikováno v:
IEEE Access, Vol 11, Pp 96449-96459 (2023)
Batch Normalization (BatchNorm) is an effective architectural component in deep learning models that helps to improve model performance and speed up training. However, it has also been found to increase the vulnerability of models to adversarial atta
Externí odkaz:
https://doaj.org/article/bec15144ef58418b9179bbe73c999749
Autor:
Awais Muhammad, Sung-Ho Bae
Publikováno v:
IEEE Access, Vol 10, Pp 118815-118830 (2022)
Deep learning has revolutionized computer vision with phenomenal success and widespread applications. Despite impressive results in complex problems, neural networks are susceptible to adversarial attacks: small and imperceptible changes in input spa
Externí odkaz:
https://doaj.org/article/98230c1162e74412b6321fa6466cd721
Contrastive learning, a prominent approach to representation learning, traditionally assumes positive pairs are closely related samples (the same image or class) and negative pairs are distinct samples. We challenge this assumption by proposing to le
Externí odkaz:
http://arxiv.org/abs/2410.18200
Autor:
Awais, Muhammad, Alharthi, Ali Husain Salem Abdulla, Kumar, Amandeep, Cholakkal, Hisham, Anwer, Rao Muhammad
Significant progress has been made in advancing large multimodal conversational models (LMMs), capitalizing on vast repositories of image-text data available online. Despite this progress, these models often encounter substantial domain gaps, hinderi
Externí odkaz:
http://arxiv.org/abs/2410.08405
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
In most existing multi-view modeling scenarios, cross-view correspondence (CVC) between instances of the same target from different views, like paired image-text data, is a crucial prerequisite for effortlessly deriving a consistent representation. N
Externí odkaz:
http://arxiv.org/abs/2409.14882
Autor:
Shoaib Muhammad, Ali Faizan, Awais Muhammad, Naz Iqra, Shamim Robicca, Nisar Kottakkaran Sooppy, Raja Muhammad Asif Zahoor, Malik Muhammad Yousaf, Abbas Mohamed, Saleel C. Ahamed
Publikováno v:
Nanotechnology Reviews, Vol 12, Iss 1, Pp 669-22 (2023)
In nanofluids, the effect of convection in the presence of double diffusivity on a magneto couple stress fluid with the peristaltic flow of a model in a non-uniform channel (MCSFM) is reviewed in this article. This research discusses MCSF in a non-un
Externí odkaz:
https://doaj.org/article/4b834c3af4ec4bd0b4938d33eebe2a5b
Autor:
Hanif, Asif, Shamshad, Fahad, Awais, Muhammad, Naseer, Muzammal, Khan, Fahad Shahbaz, Nandakumar, Karthik, Khan, Salman, Anwer, Rao Muhammad
Medical foundation models are gaining prominence in the medical community for their ability to derive general representations from extensive collections of medical image-text pairs. Recent research indicates that these models are susceptible to backd
Externí odkaz:
http://arxiv.org/abs/2408.07440