Zobrazeno 1 - 10
of 38 895
pro vyhledávání: '"A, Nasim"'
General Data Protection Regulations (GDPR) aim to safeguard individuals' personal information from harm. While full compliance is mandatory in the European Union and the California Privacy Rights Act (CPRA), it is not in other places. GDPR requires s
Externí odkaz:
http://arxiv.org/abs/2410.07182
Adjusting the control actions of a wheeled robot to eliminate oscillations and ensure smoother motion is critical in applications requiring accurate and soft movements. Fuzzy controllers enable a robot to operate smoothly while accounting for uncerta
Externí odkaz:
http://arxiv.org/abs/2409.17161
Sleep is known to be a key factor in emotional regulation and overall mental health. In this study, we explore the integration of sleep measures from the previous night into wearable-based mood recognition. To this end, we propose NapTune, a novel pr
Externí odkaz:
http://arxiv.org/abs/2409.04723
Discovering Ordinary Differential Equations (ODEs) from trajectory data is a crucial task in AI-driven scientific discovery. Recent methods for symbolic discovery of ODEs primarily rely on fixed training datasets collected a-priori, often leading to
Externí odkaz:
http://arxiv.org/abs/2409.01416
Autor:
Lan, Haoyu, Varghese, Bino A., Sheikh-Bahaei, Nasim, Sepehrband, Farshid, Toga, Arthur W, Choupan, Jeiran
Multi-center neuroimaging studies face technical variability due to batch differences across sites, which potentially hinders data aggregation and impacts study reliability.Recent efforts in neuroimaging harmonization have aimed to minimize these tec
Externí odkaz:
http://arxiv.org/abs/2409.00807
Recent advancements in the field of No-Reference Image Quality Assessment (NR-IQA) using deep learning techniques demonstrate high performance across multiple open-source datasets. However, such models are typically very large and complex making them
Externí odkaz:
http://arxiv.org/abs/2408.17057
MSLIQA: Enhancing Learning Representations for Image Quality Assessment through Multi-Scale Learning
No-Reference Image Quality Assessment (NR-IQA) remains a challenging task due to the diversity of distortions and the lack of large annotated datasets. Many studies have attempted to tackle these challenges by developing more accurate NR-IQA models,
Externí odkaz:
http://arxiv.org/abs/2408.16879
Semantic role labeling is a crucial task in natural language processing, enabling better comprehension of natural language. However, the lack of annotated data in multiple languages has posed a challenge for researchers. To address this, a deep learn
Externí odkaz:
http://arxiv.org/abs/2408.15896
Recent advances in deep learning have completely transformed the domain of computational pathology (CPath). More specifically, it has altered the diagnostic workflow of pathologists by integrating foundation models (FMs) and vision-language models (V
Externí odkaz:
http://arxiv.org/abs/2408.14496
Scientific Machine Learning is transforming traditional engineering industries by enhancing the efficiency of existing technologies and accelerating innovation, particularly in modeling chemical reactions. Despite recent advancements, the issue of so
Externí odkaz:
http://arxiv.org/abs/2408.10720