Results 111 to 120 of about 252,636 (309)
Arthritis Care &Research, EarlyView.People with systemic autoimmune and rheumatic diseases (SARDs) are at higher risk than the general population of experiencing adverse pregnancy and perinatal outcomes such as preeclampsia, intrauterine growth restriction, and maternal and/or fetal death.
Mehret Birru Talabi, Sonya Borrero
wiley +1 more source
Arthritis Care &Research, EarlyView.Systemic sclerosis (SSc) is a rare autoimmune disease defined by immune dysregulation, vasculopathy, and progressive fibrosis of the skin and internal organs. Despite advances in care, major complications such as interstitial lung disease (ILD) and myocardial involvement remain the leading causes of morbidity and mortality.
Cristiana Sieiro Santos +2 more
wiley +1 more source
CycleGAN Variants for Industrial Defect Data Augmentation [PDF]
ITM Web of ConferencesIndustrial visual inspection is constrained by scarce labeled defect samples and complex surface patterns in bearings, steel, and ICs, significantly hindering deep learning detection models.
Xu Xiaoyu
doaj +1 more source
β‐Catenin/c‐Myc Axis Modulates Autophagy Response to Different Ammonia Concentrations
Advanced Biology, Volume 9, Issue 3, March 2025.Ammonia, detoxified by the liver into urea and glutamine, impacts autophagy differently at varying levels. Low ammonia activates autophagy via c‐Myc and β‐catenin, while high levels suppress it. Using Huh7 cells and Spf‐ash mice, c‐Myc's role in cytoprotective autophagy is revealed, offering insights into hyperammonemia and potential therapeutic ...
S. Sergio +11 more
wiley +1 more source
DiffuWaste: Data Augmentation using Diffusion Model for Waste Semantic Segmentation [PDF]
openRecent progress in text-to-image and image-to-image generation models have resulted in the development of sophisticated systems capable of generating highly realistic and detailed images. These models have become more accessible, enabling researchers
SAMBIN, LUCA
core
A Data Augmentation Approach to Distracted Driving Detection
, 2020 Distracted driving behavior has become a leading cause of vehicle crashes. This paper proposes a data augmentation method for distracted driving detection based on the driving operation area. First, the class activation mapping method is used to show the
Jun Zhang +3 more
core +1 more source
TATS: toolbox for time series data augmentation [PDF]
PeerJ Computer ScienceAugmenting time series data plays a crucial role in enhancing the generalization of classification models, especially in scenarios where labeled datasets are limited.
Dawid Warchoł, Mariusz Oszust
doaj +2 more sources
Data Augmentation for Traffic Classification
Data Augmentation (DA) -- enriching training data by adding synthetic samples -- is a technique widely adopted in Computer Vision (CV) and Natural Language Processing (NLP) tasks to improve models performance. Yet, DA has struggled to gain traction in networking contexts, particularly in Traffic Classification (TC) tasks.
Chao Wang 0103 +4 more
openaire +2 more sources
What Do Large Language Models Know About Materials?
Advanced Engineering Materials, EarlyView.If large language models (LLMs) are to be used inside the material discovery and engineering process, they must be benchmarked for the accurateness of intrinsic material knowledge. The current work introduces 1) a reasoning process through the processing–structure–property–performance chain and 2) a tool for benchmarking knowledge of LLMs concerning ...
Adrian Ehrenhofer +2 more
wiley +1 more source
DiagnosticsBackground/Objectives: Rib fracture detection holds critical importance in the field of medical image processing. Methods: In this study, two different data augmentation methods, traditional data augmentation (Albumentations) and focused data ...
Mehmet Çağrı Göktekin +7 more
doaj +1 more source