Zobrazeno 1 - 10
of 2 451 751
pro vyhledávání: '"A, Ali"'
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
Autor:
Ramzan, Muhammad Umer, Zia, Ali, Khamis, Abdelwahed, Elgharabawy, yman, Liaqat, Ahmad, Ali, Usman
This paper presents a novel deep-learning framework that significantly enhances the transformation of rudimentary face sketches into high-fidelity colour images. Employing a Convolutional Block Attention-based Auto-encoder Network (CA2N), our approac
Externí odkaz:
http://arxiv.org/abs/2411.19005
Modern sequence models (e.g., Transformers, linear RNNs, etc.) emerged as dominant backbones of recent deep learning frameworks, mainly due to their efficiency, representational power, and/or ability to capture long-range dependencies. Adopting these
Externí odkaz:
http://arxiv.org/abs/2411.15671
Federated Learning (FL) is a distributed learning technique that maintains data privacy by providing a decentralized training method for machine learning models using distributed big data. This promising Federated Learning approach has also gained po
Externí odkaz:
http://arxiv.org/abs/2411.05173
In this research, we define two concepts; random matrix and mean square stability. Studying the stability of solutions for perturbed random differential systems is included. Partial moments of the second order were verified, which determines the stab
Externí odkaz:
http://arxiv.org/abs/2411.04929
In this study, we investigate the performance of the sparse identification of nonlinear dynamics (SINDy) algorithm and the neural ordinary differential equations (ODEs) in identification of the underlying mechanisms of open ocean Lagrangian drifter h
Externí odkaz:
http://arxiv.org/abs/2411.04350
Autor:
Zhiany, Saeed, Ghassemi, Fatemeh, Abbasimoghadam, Nesa, Hodaei, Ali, Ataollahi, Ali, Kovács, József, Ábrahám, Erika, Sirjani, Marjan
Hybrid Rebeca is introduced for modeling asynchronous event-based Cyber-Physical Systems (CPSs). In this work, we extend Hybrid Rebeca to allow the modeling of non-deterministic time behavior. We provide a set of rules to define the semantic model of
Externí odkaz:
http://arxiv.org/abs/2411.03160
This paper introduces a real-time Vehicle Collision Avoidance System (V-CAS) designed to enhance vehicle safety through adaptive braking based on environmental perception. V-CAS leverages the advanced vision-based transformer model RT-DETR, DeepSORT
Externí odkaz:
http://arxiv.org/abs/2411.01963
Evaluating datasets in data marketplaces, where the buyer aim to purchase valuable data, is a critical challenge. In this paper, we introduce an innovative task-agnostic data valuation method called PriArTa which is an approach for computing the dist
Externí odkaz:
http://arxiv.org/abs/2411.00745
Current work includes a study of the very rare case called intruder nuclear levels, where there are only seven nuclei in nature. Such cases occur when the first excited state is . The current study included only three nuclei: . The nuclear model used
Externí odkaz:
http://arxiv.org/abs/2410.20566