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Handling Inter-Annotator Agreement for Automated Skin Lesion
  Segmentation

Handling Inter-Annotator Agreement for Automated Skin Lesion Segmentation

6 June 2019
Vinícius Ribeiro
Sandra Avila
Eduardo Valle
ArXiv (abs)PDFHTML

Papers citing "Handling Inter-Annotator Agreement for Automated Skin Lesion Segmentation"

8 / 8 papers shown
What Can We Learn from Inter-Annotator Variability in Skin Lesion Segmentation?
What Can We Learn from Inter-Annotator Variability in Skin Lesion Segmentation?
Kumar Abhishek
J. Kawahara
Ghassan Hamarneh
185
1
0
12 Aug 2025
Label Convergence: Defining an Upper Performance Bound in Object Recognition through Contradictory Annotations
Label Convergence: Defining an Upper Performance Bound in Object Recognition through Contradictory AnnotationsIEEE Workshop/Winter Conference on Applications of Computer Vision (WACV), 2024
David Tschirschwitz
Volker Rodehorst
364
4
0
14 Sep 2024
MSE-Nets: Multi-annotated Semi-supervised Ensemble Networks for
  Improving Segmentation of Medical Image with Ambiguous Boundaries
MSE-Nets: Multi-annotated Semi-supervised Ensemble Networks for Improving Segmentation of Medical Image with Ambiguous Boundaries
Shuai Wang
Tengjin Weng
Jingyi Wang
Yang Shen
Zhidong Zhao
Yixiu Liu
Pengfei Jiao
Zhiming Cheng
Yaqi Wang
218
1
0
17 Nov 2023
Modeling Annotator Preference and Stochastic Annotation Error for
  Medical Image Segmentation
Modeling Annotator Preference and Stochastic Annotation Error for Medical Image Segmentation
Zehui Liao
Shishuai Hu
Yutong Xie
Yong-quan Xia
290
28
0
26 Nov 2021
Semantic Segmentation with Generative Models: Semi-Supervised Learning
  and Strong Out-of-Domain Generalization
Semantic Segmentation with Generative Models: Semi-Supervised Learning and Strong Out-of-Domain GeneralizationComputer Vision and Pattern Recognition (CVPR), 2021
Daiqing Li
Junlin Yang
Karsten Kreis
Antonio Torralba
Sanja Fidler
GANMedIm
376
225
0
12 Apr 2021
D-LEMA: Deep Learning Ensembles from Multiple Annotations -- Application
  to Skin Lesion Segmentation
D-LEMA: Deep Learning Ensembles from Multiple Annotations -- Application to Skin Lesion Segmentation
Z. Mirikharaji
Kumar Abhishek
S. Izadi
Ghassan Hamarneh
310
37
0
14 Dec 2020
Less is More: Sample Selection and Label Conditioning Improve Skin
  Lesion Segmentation
Less is More: Sample Selection and Label Conditioning Improve Skin Lesion Segmentation
Vinícius Ribeiro
Sandra Avila
Eduardo Valle
234
14
0
28 Apr 2020
Print Defect Mapping with Semantic Segmentation
Print Defect Mapping with Semantic SegmentationIEEE Workshop/Winter Conference on Applications of Computer Vision (WACV), 2020
A. C. Valente
Cristina Wada
Deangela Neves
Deangeli Neves
Fábio Perez
Guilherme A. S. Megeto
Marcos H. Cascone
Otavio Gomes
Qian Lin
UQCV
162
14
0
27 Jan 2020
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