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pro vyhledávání: '"Ahmed, M A"'
Autor:
Smith, C. Estelle, Shiekh, Kylee, Cooreman, Hayden, Rahman, Sharfi, Zhu, Yifei, Siam, Md Kamrul, Ivanitskiy, Michael, Ahmed, Ahmed M., Hallinan, Michael, Grisak, Alexander, Fierro, Gabe
Because of the rapid development and increasing public availability of Generative Artificial Intelligence (GenAI) models and tools, educational institutions and educators must immediately reckon with the impact of students using GenAI. There is limit
Externí odkaz:
http://arxiv.org/abs/2411.11166
Autor:
Soliman, Abdelrhman Y., Nor, Ahmed M., Fratu, Octavian, Halunga, Simona, Omer, Osama A., Mubark, Ahmed S.
Every year, humanity loses about 1.5 million persons due to diabetic disease. Therefore continuous monitoring of diabetes is highly needed, but the conventional approach, i.e., fingertip pricking, causes mental and physical pain to the patient. This
Externí odkaz:
http://arxiv.org/abs/2411.11094
Publikováno v:
Europhysics Letters, 141(6), 64002 (2023)
This work focuses on the study of identified hadrons and strange hadrons, recorded by CMS, and light nuclei and their anti-nuclei, recorded by ALICE, at 0.9 TeV, 2.76 TeV, 7 TeV and 13 TeV centre of mass energies in pp collision at mid rapidities. Th
Externí odkaz:
http://arxiv.org/abs/2411.08669
Integrated sensing and communications (ISAC) has emerged as a means to efficiently utilize spectrum and thereby save cost and power. At the higher end of the spectrum, ISAC systems operate at wideband using large antenna arrays to meet the stringent
Externí odkaz:
http://arxiv.org/abs/2411.02827
Mixed-precision quantization works Neural Networks (NNs) are gaining traction for their efficient realization on the hardware leading to higher throughput and lower energy. In-Memory Computing (IMC) accelerator architectures are offered as alternativ
Externí odkaz:
http://arxiv.org/abs/2411.01417
Autor:
Salih, Ahmed M
Explainable Artificial Intelligence (XAI) emerged to reveal the internal mechanism of machine learning models and how the features affect the prediction outcome. Collinearity is one of the big issues that XAI methods face when identifying the most in
Externí odkaz:
http://arxiv.org/abs/2411.00846
Autor:
Nazar, Ahmad M., Celik, Abdulkadir, Selim, Mohamed Y., Abdallah, Asmaa, Qiao, Daji, Eltawil, Ahmed M.
Large language models (LLMs) hold significant promise in advancing network management and orchestration in 6G and beyond networks. However, existing LLMs are limited in domain-specific knowledge and their ability to handle multi-modal sensory data, w
Externí odkaz:
http://arxiv.org/abs/2410.18104
Autor:
Salih, Ahmed M
Data pre-processing is a significant step in machine learning to improve the performance of the model and decreases the running time. This might include dealing with missing values, outliers detection and removing, data augmentation, dimensionality r
Externí odkaz:
http://arxiv.org/abs/2409.00155
Object detection is crucial in various cutting-edge applications, such as autonomous vehicles and advanced robotics systems, primarily relying on data from conventional frame-based RGB sensors. However, these sensors often struggle with issues like m
Externí odkaz:
http://arxiv.org/abs/2408.05321
Autor:
Li, Qilei, Abdelmoniem, Ahmed M.
Federated Learning (FL) is a distributed machine learning diagram that enables multiple clients to collaboratively train a global model without sharing their private local data. However, FL systems are vulnerable to attacks that are happening in mali
Externí odkaz:
http://arxiv.org/abs/2408.02813