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Sang-Hyun Lee

3 papers indexed

arxivcs.AI2026-06-29

Domain Adaptation with Adaptive Imagination for Visual Reinforcement Learning under Limited Target Data

Hyunwoo Park, Sang-Hyun Lee

Sim-to-real transfer remains a major obstacle for reinforcement learning (RL), especially for vision-based control where image observations exacerbate the state-distribution shift between simulation and the real world. Domain adaptation (DA) is a promising remedy for this challen…

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arxivcs.CV2026-06-28

Rectifying Mask via Entropy for Distractor-Free 3DGS in Ambiguous Scenarios

Wongi Park, Jiyeon Lim, Minjae Lee, Myeongseok Nam, Seongjun Choi, Jungwoo Kim, et al.

We present RefineSplat, a systematic framework that effectively constructs transient masks to identify diverse ambiguous distractors. To do this, we qualitatively and quantitatively analyze issues and propose a novel entropy-aware adaptive masking method. Unlike existing approach…

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crossrefApplied Sciences2023-08-10Cited by 11

Performance Evaluation of Machine Learning and Deep Learning-Based Models for Predicting Remaining Capacity of Lithium-Ion Batteries

Sang-Hyun Lee

Lithium-ion batteries are widely used in electric vehicles, smartphones, and energy storage devices due to their high power and light weight. The goal of this study is to predict the remaining capacity of a lithium-ion battery and evaluate its performance through three machine le…

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