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researcher

K. Paeng

3 papers here

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

author position
  • middle author1
  • last author2

Across the 3 of 3 papers where every author was matched, so the position is known.

fields
  • cs.CV3

identity via Semantic Scholar / OpenAlex

most citedPseudoEdgeNet: Nuclei Segmentation only with Point Annotations

8 citations · 8 across the 1 of their papers we have counts for

collaborators

3 papers

cs.CV2019★ 8 cited

PseudoEdgeNet: Nuclei Segmentation only with Point Annotations

Inwan Yoo, Donggeun Yoo, Kyunghyun Paeng

Nuclei segmentation is one of the important tasks for whole slide image analysis in digital pathology. With the drastic advance of deep learning, recent deep networks have demonstr…

cs.CV2018

Predicting breast tumor proliferation from whole-slide images: the TUPAC16 challenge

Mitko Veta, Yujing J. Heng, Nikolas Stathonikos +30

Tumor proliferation is an important biomarker indicative of the prognosis of breast cancer patients. Assessment of tumor proliferation in a clinical setting is highly subjective an…

cs.CV2018

A Robust and Effective Approach Towards Accurate Metastasis Detection and pN-stage Classification in Breast Cancer

Byungjae Lee, Kyunghyun Paeng

Predicting TNM stage is the major determinant of breast cancer prognosis and treatment. The essential part of TNM stage classification is whether the cancer has metastasized to the…

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Not affiliated with arXiv. Researcher data from Semantic Scholar (ODC-BY) and OpenAlex.