Zobrazeno 1 - 10
of 59 884
pro vyhledávání: '"KABIR, A."'
Autor:
Kabir, Ehsan, Kabir, Md. Arafat, Downey, Austin R. J., Bakos, Jason D., Andrews, David, Huang, Miaoqing
Transformer neural networks (TNNs) are being applied across a widening range of application domains, including natural language processing (NLP), machine translation, and computer vision (CV). Their popularity is largely attributed to the exceptional
Externí odkaz:
http://arxiv.org/abs/2409.14023
Autor:
Ni, Jinjie, Song, Yifan, Ghosal, Deepanway, Li, Bo, Zhang, David Junhao, Yue, Xiang, Xue, Fuzhao, Zheng, Zian, Zhang, Kaichen, Shah, Mahir, Jain, Kabir, You, Yang, Shieh, Michael
Perceiving and generating diverse modalities are crucial for AI models to effectively learn from and engage with real-world signals, necessitating reliable evaluations for their development. We identify two major issues in current evaluations: (1) in
Externí odkaz:
http://arxiv.org/abs/2410.13754
As the use of web browsers continues to grow, the potential for cybercrime and web-related criminal activities also increases. Digital forensic investigators must understand how different browsers function and the critical areas to consider during we
Externí odkaz:
http://arxiv.org/abs/2410.12605
Artificial intelligence (AI) has emerged as a promising tool for predicting COVID-19 from medical images. In this paper, we propose a novel continual learning-based approach and present the design and implementation of a mobile application for screen
Externí odkaz:
http://arxiv.org/abs/2410.12589
Autor:
Rahman, Md. Sohanur, Chowdhury, Muhammad E. H., Rahman, Hasib Ryan, Ahmed, Mosabber Uddin, Kabir, Muhammad Ashad, Roy, Sanjiban Sekhar, Sarmun, Rusab
In this study, we propose a novel and robust framework, Self-DenseMobileNet, designed to enhance the classification of nodules and non-nodules in chest radiographs (CXRs). Our approach integrates advanced image standardization and enhancement techniq
Externí odkaz:
http://arxiv.org/abs/2410.12584
We study the effects of missingness on the estimation of population parameters. Moving beyond restrictive missing completely at random (MCAR) assumptions, we first formulate a missing data analogue of Huber's arbitrary $\epsilon$-contamination model.
Externí odkaz:
http://arxiv.org/abs/2410.10704
Autor:
Kabir, Adib
This study presents a numerical simulation of a quantum electron confined in a 10 nm potential well, using the Crank-Nicolson numerical technique to solve the time-dependent Schrodinger equation. The results capture the evolution of the electron's wa
Externí odkaz:
http://arxiv.org/abs/2410.10060
Publikováno v:
Chinese Journal of Physics, 87, 797-803 (2024)
The Gamow-Teller (GT) strength distributions of sd shell N=Z nuclei ($^{24}$Mg, $^{28}$Si, and $^{32}$S) are investigated within the framework of proton-neutron quasi particle random phase approximation (pn QRPA) using a deformed basis. The nuclear p
Externí odkaz:
http://arxiv.org/abs/2410.06619
The nuclear ground state properties of 67 80As nuclei have been investigated within the framework of relativistic mean field (RMF) approach. The RMF model with density dependent (DDME2) interaction is utilized for the calculation of potential energy
Externí odkaz:
http://arxiv.org/abs/2410.07578
Autor:
Kabir, MD Arafat, Kamucheka, Tendayi, Fredricks, Nathaniel, Mandebi, Joel, Bakos, Jason, Huang, Miaoqing, Andrews, David
Many recent FPGA-based Processor-in-Memory (PIM) architectures have appeared with promises of impressive levels of parallelism but with performance that falls short of expectations due to reduced maximum clock frequencies, an inability to scale proce
Externí odkaz:
http://arxiv.org/abs/2410.07546