A5101998939- Advanced Image Processing Techniques
- Machine Learning in Healthcare
- Artificial Intelligence in Healthcare
- Advanced Vision and Imaging
- Structural Response to Dynamic Loads
- GaN-based semiconductor devices and materials
- Explainable Artificial Intelligence (XAI)
- Multimodal Machine Learning Applications
- Video Analysis and Summarization
- Time Series Analysis and Forecasting
- Semiconductor Quantum Structures and Devices
- Advanced Image and Video Retrieval Techniques
- Layered Double Hydroxides Synthesis and Applications
- Polyoxometalates: Synthesis and Applications
- Concrete Corrosion and Durability
- Industrial Vision Systems and Defect Detection
- Tribology and Lubrication Engineering
- Adhesion, Friction, and Surface Interactions
- Machine Learning and Data Classification
- Health, Environment, Cognitive Aging
- Domain Adaptation and Few-Shot Learning
- Face and Expression Recognition
- Magnetic Bearings and Levitation Dynamics
- Advancements in Semiconductor Devices and Circuit Design
- Computer Graphics and Visualization Techniques
Kyungpook National University
2023
Kyung Hee University
1996-2023
This article presents the results of an experimental and analytical study on behavior concrete cylinders externally wrapped with fiber-reinforced polymer (FRP) composites internally reinforced steel spirals. The work was carried out by testing twenty-four 150 × 300 mm 2 subjected to pure compression various confinement ratios types confining material. test show that compressive response confined both FRP spirals cannot be predicted summing individual effects obtained from is largely...
The proliferation of deep learning-based machine vision applications has given rise to a new type compression, so called video coding for (VCM). VCM differs from traditional in that it is optimized performance instead human visual quality. In the feature compression track MPEG-VCM, multi-scale features extracted images are subject compression. Recent works have demonstrated versatile (VVC) standard-based approach can achieve BD-rate reduction up 96% against MPEG-VCM anchor. However, still...
Recently, video and image compression methods using neural networks have received much attention. In MPEG standardization, Video Coding for Machine (VCM) is a newly arising topic which attempts to compress features/images the purpose of machine vision tasks. Especially, compressing features has advantages in terms privacy protection computation off-loading. this paper, we propose an effective feature method equipped with super-resolution (SR) module features. Our main motivation comes from...
We propose a novel interactive learning framework which we refer to as Interactive Attention Learning (IAL), in the human supervisors interactively manipulate allocated attentions, correct model's behavior by updating attention-generating network. However, such model is prone overfitting due scarcity of annotations, and requires costly retraining. Moreover, it almost infeasible for annotators examine attentions on tons instances features. tackle these challenges proposing sample-efficient...
The third ML4H symposium was held in person on December 10, 2023, New Orleans, Louisiana, USA. included research roundtable sessions to foster discussions between participants and senior researchers timely relevant topics for the \ac{ML4H} community. Encouraged by successful virtual roundtables previous year, we organized eleven in-person four at 2022. organization of conference involved 17 Senior Chairs 19 Junior across 11 tables. Each session invited chairs (with substantial experience...
Effective, reliable, and scalable development of machine learning (ML) solutions for structured electronic health record (EHR) data requires the ability to reliably generate high-quality baseline models diverse supervised tasks in an efficient performant manner. Historically, producing such has been a largely manual effort--individual researchers would need decide on particular featurization tabularization processes apply their individual raw, longitudinal data; then train model over those...
We present RelCon, a novel self-supervised *Rel*ative *Con*trastive learning approach that uses learnable distance measure in combination with softened contrastive loss for training an motion foundation model from wearable sensors. The captures motif similarity and domain-specific semantic information such as rotation invariance. learned provides measurement of between pair accelerometer time-series segments, which is used to the anchor various other sampled candidate segments. trained on 1...
In this paper, we report scalable 5 -level stacked gate-all-around (GAA) 0.53 Ga0.47As multi-bridge channel FETs (MBCFETs), with careful attention paid to fluorine migration. At its heart, maintained temperature of all the unit process steps below 300 °C and inserted an n-InP ledge into a top ${In}_{0.52}\mathrm{Al}_{0.48}\mathrm{As}$ sacrificial layer suppress $\mathrm{F}^{-}$-induced donor passivation. addition, used selectively regrown $n+{In}_{0.53}\mathrm{Ga}_{0.47}$ As contact...
In clinical practice, one often needs to identify whether a patient is at high risk of adverse outcomes after some key medical event; for example, the short-term death an admission heart failure. This task challenging due complexity, variability, and heterogeneity longitudinal data, especially individuals suffering from chronic diseases like this paper, we introduce Event-Based Contrastive Learning (EBCL), method learning embeddings heterogeneous data that preserves temporal information...
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