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J. Song

4 papers hereh-index 25 citations7 works total

Matching runs newest-first, so older work may not be attached to this profile yet.

author position
  • first author1
  • middle author3

Across the 4 of 4 papers where every author was matched, so the position is known.

fields
  • cs.CV3
  • eess.IV1
same name
  • J. Song — 257 papers, h 14
  • J. Song — 140 papers
  • J. Song — 118 papers, h 9
  • J. Song — 103 papers, h 26
  • J. Song — 74 papers, h 8
  • J. Song — 71 papers, h 5

Either other researchers who publish under this name, or the same person where the external sources have not merged their records.

identity via Semantic Scholar / OpenAlex

collaborators

4 papers

cs.CV2026

TaxoMIL: Taxonomy-Constrained Learning for Hierarchical Whole Slide Image Analysis

Chaeyeon Lee, Khang Nguyen Quoc, Jinsol Song +3

Whole slide image (WSI) analysis is central to computational pathology, with multiple instance learning (MIL) emerging as the standard pipeline for slide-level diagnosis. However,…

cs.CV2026

Hierarchical Classification for Improved Histopathology Image Analysis

Keunho Byeon, Jinsol Song, Seong Min Hong +2

Whole-slide image analysis is essential for diagnostic tasks in pathology, yet existing deep learning methods primarily rely on flat classification, ignoring hierarchical relations…

eess.IV2025

Pathology-Informed Latent Diffusion Model for Anomaly Detection in Lymph Node Metastasis

Jiamu Wang, Keunho Byeon, Jinsol Song +4

Anomaly detection is an emerging approach in digital pathology for its ability to efficiently and effectively utilize data for disease diagnosis. While supervised learning approach…

cs.CV2025

Normal and Abnormal Pathology Knowledge-Augmented Vision-Language Model for Anomaly Detection in Pathology Images

Jinsol Song, Jiamu Wang, Anh Tien Nguyen +4

Anomaly detection in computational pathology aims to identify rare and scarce anomalies where disease-related data are often limited or missing. Existing anomaly detection methods,…

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