Hangyeul Shin

Corrigendum to “Automatic liver Couinaud segmentation from computed tomography scans with a gradient-enhanced hierarchical cascade deep learning network” [Current Problems in Surgery 75 (2026) 101957]

Seungyoo Lee, Kyujin Han, Hangyeul Shin, Seunghyon Kim et autres

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Deep Learning-Based Liver Tumor Segmentation from Computed Tomography Scans with a Gradient-Enhanced Network

Hangyeul Shin, Kyujin Han, Seungyoo Lee, Harin Park et autres

Background/Objectives: This study aimed to develop a fully automatic method for liver tumor segmentation based on our previously developed gradient-enhanced network G-UNETR++. Methods: The proposed method consists of segmentation of the full liver region from computed tomography (CT) images using G-UNETR++, masking …

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Automatic liver Couinaud segmentation from computed tomography scans with a gradient-enhanced hierarchical cascade deep learning network

Seungyoo Lee, Kyujin Han, Hangyeul Shin, Seunghyun Kim et autres

Background Couinaud segmentation is crucial to understand the anatomical and functional structures of the liver for precise surgical planning. Couinaud segmentation is a challenging task in clinical practice due to the high similarity of intensity values between different liver segments and the …

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Multi-Label Facial Emotion Classification by Efficient Network from Korean Drama Video Clips

Hangyeul Shin, Junyong Ok, Xiaopeng Yang

This paper presents an EfficientNetV2-based framework for multi-label facial emotion recognition tailored to Korean facial expressions. Unlike traditional single-label models trained on Western datasets, our method embraces the complexity of co-occurring emotions by modeling them as concurrent affective states. Utilizing a dataset …

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FFaceNeRF: Few-shot Face Editing in Neural Radiance Fields

Kwan Yun, Chaelin Kim, Hangyeul Shin, Junyong Noh

Recent 3D face editing methods using masks have produced high-quality edited images by leveraging Neural Radiance Fields (NeRF). Despite their impressive performance, existing methods often provide limited user control due to the use of pre-trained segmentation masks. To utilize masks with a …

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FFaceNeRF: Few-shot Face Editing in Neural Radiance Fields

Kwan Yun, Chaelin Kim, Hangyeul Shin, Junyong Noh

Recent 3D face editing methods using masks have produced high-quality edited images by leveraging Neural Radiance Fields (NeRF). Despite their impressive performance, existing methods often provide limited user control due to the use of pre-trained segmentation masks. To utilize masks with a …

G-UNETR++: A Gradient-Enhanced Network for Accurate and Robust Liver Segmentation from Computed Tomography Images

Seungyoo Lee, Kyujin Han, Hangyeul Shin, Harin Park et autres

Accurate liver segmentation from computed tomography (CT) scans is essential for liver cancer diagnosis and liver surgery planning. Convolutional neural network (CNN)-based models have limited segmentation performance due to their localized receptive fields. Hybrid models incorporating CNNs and transformers that can capture …

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Dynamic Modeling and Analysis of Omni-directional wheel Type Heavy-water Reactor Robot

Hangyeul Shin, S.G. Lee, B.S. Kim, Seung-Bin Moon et autres