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20242026
most citedEZ-Sort: Efficient Pairwise Comparison via Zero-Shot CLIP-Based Pre-Ordering and Human-in-the-Loop Sorting

3 citations · 4 across the 17 of their papers we have counts for

collaborators

21 papers

cs.CV2026

TRACE: Topology-Aware Reconnection via Prediction-Adaptive Connectivity Enforcement for Thin-Structure Segmentation

Junho Moon, Ikbeom Jang

Thin, elongated structures are particularly sensitive to connectivity errors, as even a few local segmentation mistakes can disrupt otherwise continuous paths. Existing skeleton-ba…

cs.LG2026

CoPoE: Multimodal Fusion via Decomposable Disease-Coordinate Product-of-Experts for Missing-Modality Alzheimer's Diagnosis

Chihun An, Ikbeom Jang

Multimodal Alzheimer's disease (AD) diagnosis benefits from integrating heterogeneous clinical, imaging, genomic, and biomarker evidence, but clinical cohorts frequently suffer fro…

cs.LG2026

MovieSTAGE: Scene, Transition, and Global Encoding for Movie-fMRI ADHD Classification

Boseong Kim, Haejun Chung, Ikbeom Jang

Naturalistic movie-fMRI provides a shared, temporally structured probe of brain dynamics, yet predictive models commonly rely on whole-run functional connectivity (FC) or temporall…

cs.LG2026

Let Confidence Change, Not the Prediction: Prediction-Preserving Repair for Post-hoc Calibration

Daehwan Kim, Haejun Chung, Ikbeom Jang

Post-hoc calibration corrects reported confidence, yet a multiclass calibrator can also change the associated top-1 prediction. Accuracy captures only the net effect of these chang…

cs.LG2026

SafeECGMatch: Calibration-Aware Joint Frequency and Time Space Semi-Supervised Learning for Open-Set ECG Classification

Hongkyu Koh, Ikbeom Jang

Electrocardiogram (ECG) classification models often suffer from severe label scarcity, making semi-supervised learning (SSL) an attractive strategy for reducing annotation costs. I…

cs.LG2026

Surprise-Guided MergeSort: Budget-Efficient Human-in-the-Loop Ranking via Adaptive Comparison Scheduling

Yujin Park, Haejun Chung, Ikbeom Jang

Pairwise comparison is the gold standard for subjective ranking tasks; however, exhaustive annotation requires a massive number of human comparisons (). While sorting-based…

cs.CV2026

MetaRanker: Human-in-the-loop Active Ranking for Metalens Image Quality

Yujin Park, Haejun Chung, Ikbeom Jang

Image quality in modern imaging systems emerges from the coupled effects of the sensor, optics, and computational reconstruction. Ultra-thin metalenses offer a path toward substant…

cs.CV2026

OTCHA: Optimal Transport-driven Confidence-aware Latent Hub Alignment for Multi-View Medical Image Classification

Jiwoong Yang, Haejun Chung, Ikbeom Jang

Multi-view imaging, such as mammography and chest radiography, is a standard component of clinical practice. However, medical images are often unregistered and contain view-specifi…

cs.LG2026

When, Where, and How: Adaptive Binning for Tabular Self-Supervised Learning

Daehwan Kim, Haejun Chung, Ikbeom Jang

Medical tabular data are ubiquitous in clinical research, but deep learning for tables remains underexplored because reliable labels often require costly expert adjudication, even…

cs.CV2026

CSWinUNETR: Segmentation of Thin Anatomical Structures in Medical Images

Junho Moon, Haejun Chung, Ikbeom Jang

Accurate segmentation of thin, tortuous anatomical structures, such as retinal vessels, cerebral vasculature, and facial wrinkles, remains challenging due to low contrast, frequent…

cs.CV2026

RAPID: Layer-Wise Redundancy-Aware Pruning and Importance-Driven Token Merging for Efficient ViT

Kyumin Choi, Ikbeom Jang

Vision Transformers (ViTs) achieve strong performance but suffer from high computational costs due to quadratic self-attention complexity. Although token reduction techniques such…

cs.CL2026

SERC: LDPC-Inspired Semantic Error Correction for Retrieval-Augmented Generation

Gyumin Kim, Juhwan Park, Jaeha Kim +3

While Large Language Models (LLMs) have demonstrated remarkable capabilities, their reliability is significantly compromised by hallucinations. Existing intrinsic self-correction m…

cs.CV2026

Dodgersort: Uncertainty-Aware VLM-Guided Human-in-the-Loop Pairwise Ranking

Yujin Park, Haejun Chung, Ikbeom Jang

Pairwise comparison labeling is emerging as it yields higher inter-rater reliability than conventional classification labeling, but exhaustive comparisons require quadratic cost. W…

cs.CV2025★ 3 cited

EZ-Sort: Efficient Pairwise Comparison via Zero-Shot CLIP-Based Pre-Ordering and Human-in-the-Loop Sorting

Yujin Park, Haejun Chung, Ikbeom Jang

Pairwise comparison is often favored over absolute rating or ordinal classification in subjective or difficult annotation tasks due to its improved reliability. However, exhaustive…

q-bio.NC2025

BOLDSimNet: Examining Brain Network Similarity between Task and Resting-State fMRI

Boseong Kim, Debashis Das Chakladar, Haejun Chung +1

Traditional causal connectivity methods in task-based and resting-state functional magnetic resonance imaging (fMRI) face challenges in accurately capturing directed information fl…

cs.CV2024

Hierarchical mutual distillation for multi-view fusion: Learning from all possible view combinations

Jiwoong Yang, Haejun Chung, Ikbeom Jang

Multi-view learning often struggles to effectively leverage images captured from diverse angles and locations. Learning methods for unstructured multi-view images remain largely un…

cs.LG2024

Ordinal-Aware Calibration for Ordinal Classification

Daehwan Kim, Haejun Chung, Ikbeom Jang

Deep neural networks frequently produce overconfident, miscalibrated predictions. In ordinal classification, predictions must also adhere to a unimodal and order-consistent structu…

cs.CV2024

Weakly Supervised Pretraining and Multi-Annotator Supervised Finetuning for Facial Wrinkle Detection

Ik Jun Moon, Junho Moon, Ikbeom Jang

1. Research question: With the growing interest in skin diseases and skin aesthetics, the ability to predict facial wrinkles is becoming increasingly important. This study aims to…

eess.IV2024★ 1 cited

Preoperative Rotator Cuff Tear Prediction from Shoulder Radiographs using a Convolutional Block Attention Module-Integrated Neural Network

Chris Hyunchul Jo, Jiwoong Yang, Byunghwan Jeon +2

Research question: We test whether a plane shoulder radiograph can be used together with deep learning methods to identify patients with rotator cuff tears as opposed to using an M…

cs.CV2024

Facial Wrinkle Segmentation for Cosmetic Dermatology: Pretraining with Texture Map-Based Weak Supervision

Junho Moon, Haejun Chung, Ikbeom Jang

Facial wrinkle detection plays a crucial role in cosmetic dermatology. Precise manual segmentation of facial wrinkles is challenging and time-consuming, with inherent subjectivity…

eess.IV2024

Cyclic 2.5D Perceptual Loss for Cross-Modal 3D Medical Image Synthesis: T1w MRI to Tau PET

Junho Moon, Symac Kim, Haejun Chung +1

Positron emission tomography (PET) provides molecular biomarkers for Alzheimer's disease and related dementias (ADRD) and is increasingly used for diagnosis, staging, and clinical…