9 citations · 11 across the 8 of their papers we have counts for
6 papers · 1 filter
Sensor Calibration Model Balancing Accuracy, Real-time, and Efficiency
Jinyong Yun, Hyungjin Kim, Seokho Ahn +2
Most on-device sensor calibration studies benchmark models only against three macroscopic requirements (i.e., accuracy, real-time, and resource efficiency), thereby hiding deployme…
Stochastic Deep Graph Clustering for Practical Group Formation
Junhyung Park, Hyungjin Kim, Seokho Ahn +1
While prior work on group recommender systems (GRSs) has primarily focused on improving recommendation accuracy, most approaches assume static or predefined groups, making them uns…
Draw Your Mind: Personalized Generation via Condition-Level Modeling in Text-to-Image Diffusion Models
Hyungjin Kim, Seokho Ahn, Young-Duk Seo
Personalized generation in T2I diffusion models aims to naturally incorporate individual user preferences into the generation process with minimal user intervention. However, exist…
SenDaL: An Effective and Efficient Calibration Framework of Low-Cost Sensors for Daily Life
Seokho Ahn, Hyungjin Kim, Euijong Lee +1
The collection of accurate and noise-free data is a crucial part of Internet of Things (IoT)-controlled environments. However, the data collected from various sensors in daily life…
UKTA: Unified Korean Text Analyzer
Seokho Ahn, Junhyung Park, Ganghee Go +5
Evaluating writing quality is complex and time-consuming often delaying feedback to learners. While automated writing evaluation tools are effective for English, Korean automated w…
RecKG: Knowledge Graph for Recommender Systems
Junhyuk Kwon, Seokho Ahn, Young-Duk Seo
Knowledge graphs have proven successful in integrating heterogeneous data across various domains. However, there remains a noticeable dearth of research on their seamless integrati…