Zobrazeno 1 - 10
of 8 896
pro vyhledávání: '"Momin, A A"'
Data heterogeneity among Federated Learning (FL) users poses a significant challenge, resulting in reduced global model performance. The community has designed various techniques to tackle this issue, among which Knowledge Distillation (KD)-based tec
Externí odkaz:
http://arxiv.org/abs/2409.19912
Artificial intelligence (AI) has the potential to revolutionize brachytherapy's clinical workflow. This review comprehensively examines the application of AI, focusing on machine learning and deep learning, in facilitating various aspects of brachyth
Externí odkaz:
http://arxiv.org/abs/2409.16543
Deep neural networks (DNNs) have made significant strides in tackling challenging tasks in wireless systems, especially when an accurate wireless model is not available. However, when available data is limited, traditional DNNs often yield subpar res
Externí odkaz:
http://arxiv.org/abs/2409.00124
Autor:
Chandio, Yasra, Khan, Momin A., Selialia, Khotso, Garcia, Luis, DeGol, Joseph, Anwar, Fatima M.
Publikováno v:
2024 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)
Autonomous robots, autonomous vehicles, and humans wearing mixed-reality headsets require accurate and reliable tracking services for safety-critical applications in dynamically changing real-world environments. However, the existing tracking approac
Externí odkaz:
http://arxiv.org/abs/2407.06889
Intelligent tutors have shown success in delivering a personalized and adaptive learning experience. However, there exist challenges regarding the granularity of knowledge in existing frameworks and the resulting instructions they can provide. To add
Externí odkaz:
http://arxiv.org/abs/2405.14716
Autor:
Kumar, Dayanand, Li, Hanrui, Singh, Amit, Rajbhar, Manoj Kumar, Syed, Abdul Momin, Lee, Hoonkyung, El-Atab, Nazek
Photoresponsivity studies of wide-bandgap oxide-based devices have emerged as a vibrant and popular research area. Researchers have explored various material systems in their quest to develop devices capable of responding to illumination. In this stu
Externí odkaz:
http://arxiv.org/abs/2404.05701
New York City (NYC) topped the global chart for the worst air pollution in June 2023, owing to the wildfire smoke drifting in from Canada. This unprecedented situation caused significant travel disruptions and shifts in traditional activity patterns
Externí odkaz:
http://arxiv.org/abs/2402.01683
This study proposes a novel method to understand the factors affecting individuals' perception of transport accessibility, socioeconomic disparity, and public infrastructure. As opposed to the time consuming and expensive survey-based approach, this
Externí odkaz:
http://arxiv.org/abs/2402.01682
Autor:
Abbas, Momin, Zhou, Yi, Ram, Parikshit, Baracaldo, Nathalie, Samulowitz, Horst, Salonidis, Theodoros, Chen, Tianyi
In-context learning (ICL) is a new paradigm for natural language processing that utilizes Generative Pre-trained Transformer (GPT)-like models. This approach uses prompts that include in-context demonstrations to generate the corresponding output for
Externí odkaz:
http://arxiv.org/abs/2401.12406
This paper considers the problem of extracting building footprints from satellite imagery -- a task that is critical for many urban planning and decision-making applications. While recent advancements in deep learning have made great strides in autom
Externí odkaz:
http://arxiv.org/abs/2311.02617