Zobrazeno 1 - 10
of 114 441
pro vyhledávání: '"A A, Ullah"'
Deep Learning Approach for Enhancing Oral Squamous Cell Carcinoma with LIME Explainable AI Technique
The goal of the present study is to analyze an application of deep learning models in order to augment the diagnostic performance of oral squamous cell carcinoma (OSCC) with a longitudinal cohort study using the Histopathological Imaging Database for
Externí odkaz:
http://arxiv.org/abs/2411.14184
Autor:
Nabi, Jameel-Un, Bayram, Tuncay, Riaz, Muhammad, Ullah, Asim, Hayder, Anes, Senturk, Sevki, Boyukata, Mahmut
Publikováno v:
Physica Scripta 98, 085314 (2023)
This study re examines the effect of nuclear deformation on the calculated Gamow Teller (GT) strength distributions of neutron deficient (178 192Hg, 185 194Pb and 196 206Po) nuclei. The nuclear ground state properties and shape parameters were calcul
Externí odkaz:
http://arxiv.org/abs/2411.18411
Autor:
Iacovelli, Giovanni, Sheemar, Chandan Kumar, Khan, Wali Ullah, Mahmood, Asad, Alexandropoulos, George C., Querol, Jorge, Chatzinotas, Symeon
In this article, we propose the integration of the Holographic Multiple Input Multiple Output (HMIMO) as a transformative solution for next generation Non-Terrestrial Networks (NTNs), addressing key challenges, such as high hardware costs, launch exp
Externí odkaz:
http://arxiv.org/abs/2411.10014
Growing concerns over the lack of transparency in AI, particularly in high-stakes fields like healthcare and finance, drive the need for explainable and trustworthy systems. While Large Language Models (LLMs) perform exceptionally well in generating
Externí odkaz:
http://arxiv.org/abs/2411.08469
This paper presents a hybrid methodology that enhances the training process of deep learning (DL) models by embedding domain expert knowledge using ontologies and answer set programming (ASP). By integrating these symbolic AI methods, we encode domai
Externí odkaz:
http://arxiv.org/abs/2411.08463
Autor:
Yi, Weixi, Wang, Yipei, Thorley, Natasha, Ng, Alexander, Punwani, Shonit, Kasivisvanathan, Veeru, Barratt, Dean C., Saeed, Shaheer Ullah, Hu, Yipeng
Current imaging-based prostate cancer diagnosis requires both MR T2-weighted (T2w) and diffusion-weighted imaging (DWI) sequences, with additional sequences for potentially greater accuracy improvement. However, measuring diffusion patterns in DWI se
Externí odkaz:
http://arxiv.org/abs/2411.07416
Graph convolutional networks (GCNs) are an effective skeleton-based human action recognition (HAR) technique. GCNs enable the specification of CNNs to a non-Euclidean frame that is more flexible. The previous GCN-based models still have a lot of issu
Externí odkaz:
http://arxiv.org/abs/2411.06553
Privacy-preserving and secure data sharing are critical for medical image analysis while maintaining accuracy and minimizing computational overhead are also crucial. Applying existing deep neural networks (DNNs) to encrypted medical data is not alway
Externí odkaz:
http://arxiv.org/abs/2411.05901
Autor:
Goldberg, Alexander, Ullah, Ihsan, Khuong, Thanh Gia Hieu, Rachmat, Benedictus Kent, Xu, Zhen, Guyon, Isabelle, Shah, Nihar B.
Large language models (LLMs) represent a promising, but controversial, tool in aiding scientific peer review. This study evaluates the usefulness of LLMs in a conference setting as a tool for vetting paper submissions against submission standards. We
Externí odkaz:
http://arxiv.org/abs/2411.03417
Autor:
Shah, Syed Najaf Haider, Semper, Sebastian, Khan, Aamir Ullah, Schneider, Christian, Robert, Joerg
Integrated Sensing and Communication (ISAC) is a technology paradigm that combines sensing capabilities with communication functionalities in a single device or system. In vehicle-to-everything (V2X) sidelink, ISAC can provide enhanced safety by allo
Externí odkaz:
http://arxiv.org/abs/2411.03191