Zobrazeno 1 - 10
of 61 555
pro vyhledávání: '"Wahab, A. A."'
Autor:
Ramzan, Muhammad Umer, Khaddim, Wahab, Rana, Muhammad Ehsan, Ali, Usman, Ali, Manohar, Hassan, Fiaz ul, Mehmood, Fatima
This research paper addresses the significant challenge of accurately estimating poverty levels using deep learning, particularly in developing regions where traditional methods like household surveys are often costly, infrequent, and quickly become
Externí odkaz:
http://arxiv.org/abs/2411.19690
With the widespread of digital environments, reliable authentication and continuous access control has become crucial. It can minimize cyber attacks and prevent frauds, specially those associated with identity theft. A particular interest lies on key
Externí odkaz:
http://arxiv.org/abs/2411.07224
In the digital age, the exposure of sensitive information poses a significant threat to security. Leveraging the ubiquitous nature of code-sharing platforms like GitHub and BitBucket, developers often accidentally disclose credentials and API keys, g
Externí odkaz:
http://arxiv.org/abs/2410.23657
Autor:
Wahab, Abdul, Khan, Tariq Mahmood, Iqbal, Shahzaib, AlShammari, Bandar, Alhaqbani, Bandar, Razzak, Imran
Identification of suspects based on partial and smudged fingerprints, commonly referred to as fingermarks or latent fingerprints, presents a significant challenge in the field of fingerprint recognition. Although fixed-length embeddings have shown ef
Externí odkaz:
http://arxiv.org/abs/2409.11802
In this paper, we evaluate the viability of CubeSats as an attractive platform for lightweight instrumentation by describing a proof of concept CubeSat that houses an astrophotonic chip for transit spectroscopy-based exoplanet atmosphere gas sensing.
Externí odkaz:
http://arxiv.org/abs/2408.06454
This paper is devoted to studying the optical and thermal geometrical properties of Hot, NUT-KerrNewman-Kasuya-AdS black hole (BH). This BH is characterized by the NUT charge and a parameter Q that comprises the electric and magnetic charge. We compu
Externí odkaz:
http://arxiv.org/abs/2408.04365
Autor:
Wehbi, Osama, Arisdakessian, Sarhad, Guizani, Mohsen, Wahab, Omar Abdel, Mourad, Azzam, Otrok, Hadi, khzaimi, Hoda Al, Ouni, Bassem
Federated learning is a promising collaborative and privacy-preserving machine learning approach in data-rich smart cities. Nevertheless, the inherent heterogeneity of these urban environments presents a significant challenge in selecting trustworthy
Externí odkaz:
http://arxiv.org/abs/2405.00394
Critical Infrastructure Facilities (CIFs), such as healthcare and transportation facilities, are vital for the functioning of a community, especially during large-scale emergencies. In this paper, we explore a potential application of Large Language
Externí odkaz:
http://arxiv.org/abs/2404.14432
This article assesses the effectiveness of current cybersecurity regulations and policies in the United States amidst the escalating frequency and sophistication of cyber threats. The focus is on the comprehensive framework established by the U.S. go
Externí odkaz:
http://arxiv.org/abs/2404.11473
Autor:
Leinonen, Tuija, Wong, David, Vasankari, Antti, Wahab, Ali, Nadarajah, Ramesh, Kaisti, Matti, Airola, Antti
Publikováno v:
Computers in Biology and Medicine, 183, 109271 (2024)
Traditionally, machine learning-based clinical prediction models have been trained and evaluated on patient data from a single source, such as a hospital. Cross-validation methods can be used to estimate the accuracy of such models on new patients or
Externí odkaz:
http://arxiv.org/abs/2403.15012