Zobrazeno 1 - 10
of 1 260 968
pro vyhledávání: '"A Mohamed A"'
Autor:
Safa, Omar M., Abdelaziz, Mahmoud M., Eltawy, Mustafa, Mamdouh, Mohamed, Gharib, Moamen, Eltenihy, Salaheldin, Ghanem, Nagia M., Ismail, Mohamed M.
Machine Unlearning has emerged as a critical area in artificial intelligence, addressing the need to selectively remove learned data from machine learning models in response to data privacy regulations. This paper provides a comprehensive comparative
Externí odkaz:
http://arxiv.org/abs/2412.19583
Autor:
Shareef, T. H. Mohamed Ahadu, Navabshan, Irfan, Masood, M Mohamed Divan, Yuvaraj, T. Eswara, Sherif, A.
Publikováno v:
J.Hasty Results 1 (2008) 1-9; Erratum: J.Hasty Results 2 (2008) 1-2
This study examines the phytochemical characteristics of Ayurvedic products. An analysis was performed on Kottakkal Ayurveda Triphala (T), Kottakkal Ayurveda Hinguvachadi Churnam (H), and Kottakkal Ayurveda Jirakadyarishtam (J) using GC-MS and LC-MS
Externí odkaz:
http://arxiv.org/abs/2412.17005
Understanding the deep meanings of the Qur'an and bridging the language gap between modern standard Arabic and classical Arabic is essential to improve the question-and-answer system for the Holy Qur'an. The Qur'an QA 2023 shared task dataset had a l
Externí odkaz:
http://arxiv.org/abs/2412.11431
Large language models (LLMs) have significantly advanced natural language processing, excelling in areas like text generation, summarization, and question-answering. Despite their capabilities, these models face challenges when fine-tuned on small, d
Externí odkaz:
http://arxiv.org/abs/2412.15254
Autor:
Sennary, Mohamed, Rivera-Dean, Javier, ElKabbash, Mohamed, Pervak, Vladimir, Lewenstein, Maciej, Hassan, Mohammed Th.
Advancements in quantum optics and squeezed light generation have revolutionized various fields of quantum science over the past three decades, with notable applications such as gravitational wave detection. Here, we extend the use of squeezed light
Externí odkaz:
http://arxiv.org/abs/2412.08881
Autor:
Belaloui, Nacer Eddine, Tounsi, Abdellah, Khamadja, Rabah Abdelmouheymen, Louamri, Mohamed Messaoud, Benslama, Achour, Neira, David E. Bernal, Rouabah, Mohamed Taha
While numerical simulations are presented in most papers introducing new methods to enhance the VQE performance, comprehensive, comparative, and applied studies remain relatively rare. We present a comprehensive, yet concise guide for the implementat
Externí odkaz:
http://arxiv.org/abs/2412.02606
Autor:
Wahid, Kareem A., Dede, Cem, El-Habashy, Dina M., Kamel, Serageldin, Rooney, Michael K., Khamis, Yomna, Abdelaal, Moamen R. A., Ahmed, Sara, Corrigan, Kelsey L., Chang, Enoch, Dudzinski, Stephanie O., Salzillo, Travis C., McDonald, Brigid A., Mulder, Samuel L., McCullum, Lucas, Alakayleh, Qusai, Sjogreen, Carlos, He, Renjie, Mohamed, Abdallah S. R., Lai, Stephen Y., Christodouleas, John P., Schaefer, Andrew J., Naser, Mohamed A., Fuller, Clifton D.
Magnetic resonance (MR)-guided radiation therapy (RT) is enhancing head and neck cancer (HNC) treatment through superior soft tissue contrast and longitudinal imaging capabilities. However, manual tumor segmentation remains a significant challenge, s
Externí odkaz:
http://arxiv.org/abs/2411.18585
Variational autoencoder (VAE) is one of the most common techniques in the field of medical image generation, where this architecture has shown advanced researchers in recent years and has developed into various architectures. VAE has advantages inclu
Externí odkaz:
http://arxiv.org/abs/2411.07348
Autor:
Mohamed, Youssef, Li, Runjia, Ahmad, Ibrahim Said, Haydarov, Kilichbek, Torr, Philip, Church, Kenneth Ward, Elhoseiny, Mohamed
Research in vision and language has made considerable progress thanks to benchmarks such as COCO. COCO captions focused on unambiguous facts in English; ArtEmis introduced subjective emotions and ArtELingo introduced some multilinguality (Chinese and
Externí odkaz:
http://arxiv.org/abs/2411.03769
Autor:
Abo-eleneen, Amr, Helmy, Menna, Abdellatif, Alaa Awad, Erbad, Aiman, Mohamed, Amr, Abdallah, Mohamed
In the face of increasing demand for zero-touch networks to automate network management and operations, two pivotal concepts have emerged: "Learn to Slice" (L2S) and "Slice to Learn" (S2L). L2S involves leveraging Artificial intelligence (AI) techniq
Externí odkaz:
http://arxiv.org/abs/2411.03686