2 citations · 3 across the 8 of their papers we have counts for
9 papers
SARIF: Segment Anything for Robust Image Forensics
Dong-Hyun Moon, Ju-Hyeon Nam, Sang-Chul Lee
Image forgery localization remains challenging due to diverse manipulation techniques and distribution shifts. Existing forgery localization models achieve high accuracy on benchma…
EcoScaleNet: A Lightweight Multi Kernel Network for Long Sequence 12 lead ECG Classification
Dong-Hyeon Kang, Ju-Hyeon Nam, Sang-Chul Lee
Accurate interpretation of 12 lead electrocardiograms (ECGs) is critical for early detection of cardiac abnormalities, yet manual reading is error prone and existing CNN based clas…
M2SFormer: Multi-Spectral and Multi-Scale Attention with Edge-Aware Difficulty Guidance for Image Forgery Localization
Ju-Hyeon Nam, Dong-Hyun Moon, Sang-Chul Lee
Image editing techniques have rapidly advanced, facilitating both innovative use cases and malicious manipulation of digital images. Deep learning-based methods have recently achie…
Test-Time Modality Generalization for Medical Image Segmentation
Ju-Hyeon Nam, Sang-Chul Lee
Generalizable medical image segmentation is essential for ensuring consistent performance across diverse unseen clinical settings. However, existing methods often overlook the capa…
TransGUNet: Transformer Meets Graph-based Skip Connection for Medical Image Segmentation
Ju-Hyeon Nam, Nur Suriza Syazwany, Sang-Chul Lee
Skip connection engineering is primarily employed to address the semantic gap between the encoder and decoder, while also integrating global dependencies to understand the relation…
VizECGNet: Visual ECG Image Network for Cardiovascular Diseases Classification with Multi-Modal Training and Knowledge Distillation
Ju-Hyeon Nam, Seo-Hyung Park, Su Jung Kim +1
An electrocardiogram (ECG) captures the heart's electrical signal to assess various heart conditions. In practice, ECG data is stored as either digitized signals or printed images.…
Modality-agnostic Domain Generalizable Medical Image Segmentation by Multi-Frequency in Multi-Scale Attention
Ju-Hyeon Nam, Nur Suriza Syazwany, Su Jung Kim +1
Generalizability in deep neural networks plays a pivotal role in medical image segmentation. However, deep learning-based medical image analyses tend to overlook the importance of…
M3FPolypSegNet: Segmentation Network with Multi-frequency Feature Fusion for Polyp Localization in Colonoscopy Images
Ju-Hyeon Nam, Seo-Hyeong Park, Nur Suriza Syazwany +3
Polyp segmentation is crucial for preventing colorectal cancer a common type of cancer. Deep learning has been used to segment polyps automatically, which reduces the risk of misdi…
Temporal Feedback Convolutional Recurrent Neural Networks for Speech Command Recognition
Taejun Kim, Juhan Nam
End-to-end learning models using raw waveforms as input have shown superior performances in many audio recognition tasks. However, most model architectures are based on convolution…