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Learning From Noisy Labels By Regularized Estimation Of Annotator
  Confusion

Learning From Noisy Labels By Regularized Estimation Of Annotator Confusion

10 February 2019
Ryutaro Tanno
A. Saeedi
S. Sankaranarayanan
Daniel C. Alexander
N. Silberman
    NoLa
ArXivPDFHTML

Papers citing "Learning From Noisy Labels By Regularized Estimation Of Annotator Confusion"

31 / 31 papers shown
Title
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 Annotations
David Tschirschwitz
Volker Rodehorst
26
1
0
14 Sep 2024
Learning from Noisy Labels for Long-tailed Data via Optimal Transport
Learning from Noisy Labels for Long-tailed Data via Optimal Transport
Mengting Li
Chuang Zhu
42
0
0
07 Aug 2024
Mixture of Experts based Multi-task Supervise Learning from Crowds
Mixture of Experts based Multi-task Supervise Learning from Crowds
Tao Han
Huaixuan Shi
Xinyi Ding
Xiao Ma
Huamao Gu
Yili Fang
30
0
0
18 Jul 2024
FedDiv: Collaborative Noise Filtering for Federated Learning with Noisy
  Labels
FedDiv: Collaborative Noise Filtering for Federated Learning with Noisy Labels
Jichang Li
Guanbin Li
Hui Cheng
Zicheng Liao
Yizhou Yu
FedML
32
15
0
19 Dec 2023
SILT: Shadow-aware Iterative Label Tuning for Learning to Detect Shadows
  from Noisy Labels
SILT: Shadow-aware Iterative Label Tuning for Learning to Detect Shadows from Noisy Labels
Han Yang
Tianyu Wang
Xiao Hu
Chi-Wing Fu
NoLa
51
13
0
23 Aug 2023
Multi-annotator Deep Learning: A Probabilistic Framework for
  Classification
Multi-annotator Deep Learning: A Probabilistic Framework for Classification
M. Herde
Denis Huseljic
Bernhard Sick
25
9
0
05 Apr 2023
Knockoffs-SPR: Clean Sample Selection in Learning with Noisy Labels
Knockoffs-SPR: Clean Sample Selection in Learning with Noisy Labels
Yikai Wang
Yanwei Fu
Xinwei Sun
NoLa
55
8
0
02 Jan 2023
Learning Confident Classifiers in the Presence of Label Noise
Learning Confident Classifiers in the Presence of Label Noise
Asma Ahmed Hashmi
Aigerim Zhumabayeva
Nikita Kotelevskii
A. Agafonov
Mohammad Yaqub
Maxim Panov
Martin Takávc
NoLa
61
2
0
02 Jan 2023
Multi-rater Prism: Learning self-calibrated medical image segmentation
  from multiple raters
Multi-rater Prism: Learning self-calibrated medical image segmentation from multiple raters
Junde Wu
Huihui Fang
Yehui Yang
Yuanpei Liu
Jing Gao
Lixin Duan
Weihua Yang
Yanwu Xu
16
2
0
01 Dec 2022
The Dynamic of Consensus in Deep Networks and the Identification of
  Noisy Labels
The Dynamic of Consensus in Deep Networks and the Identification of Noisy Labels
Daniel Shwartz
Uri Stern
D. Weinshall
NoLa
33
2
0
02 Oct 2022
A Semi-Supervised Algorithm for Improving the Consistency of
  Crowdsourced Datasets: The COVID-19 Case Study on Respiratory Disorder
  Classification
A Semi-Supervised Algorithm for Improving the Consistency of Crowdsourced Datasets: The COVID-19 Case Study on Respiratory Disorder Classification
Lara Orlandic
T. Teijeiro
David Atienza
41
9
0
09 Sep 2022
Robust Node Classification on Graphs: Jointly from Bayesian Label
  Transition and Topology-based Label Propagation
Robust Node Classification on Graphs: Jointly from Bayesian Label Transition and Topology-based Label Propagation
Jun Zhuang
M. Hasan
36
20
0
21 Aug 2022
Calibrate the inter-observer segmentation uncertainty via
  diagnosis-first principle
Calibrate the inter-observer segmentation uncertainty via diagnosis-first principle
Junde Wu
Huihui Fang
Hoayi Xiong
Lixin Duan
Mingkui Tan
Weihua Yang
Huiying Liu
Yanwu Xu
MedIm
41
1
0
05 Aug 2022
Placenta Segmentation in Ultrasound Imaging: Addressing Sources of
  Uncertainty and Limited Field-of-View
Placenta Segmentation in Ultrasound Imaging: Addressing Sources of Uncertainty and Limited Field-of-View
V. Zimmer
A. Gómez
E. Skelton
Robert Wright
G. Wheeler
...
Jacqueline Matthew
Bernhard Kainz
Daniel Rueckert
Joseph V. Hajnal
J. Schnabel
25
22
0
29 Jun 2022
Learning from Pixel-Level Noisy Label : A New Perspective for Light
  Field Saliency Detection
Learning from Pixel-Level Noisy Label : A New Perspective for Light Field Saliency Detection
Mingtao Feng
Li-Yu Daisy Liu
Liangkai Zhang
Hongshan Yu
Yaonan Wang
Ajmal Saeed Mian
24
18
0
28 Apr 2022
Sketching without Worrying: Noise-Tolerant Sketch-Based Image Retrieval
Sketching without Worrying: Noise-Tolerant Sketch-Based Image Retrieval
A. Bhunia
Subhadeep Koley
Abdullah Faiz Ur Rahman Khilji
Aneeshan Sain
Pinaki Nath Chowdhury
Tao Xiang
Yi-Zhe Song
AAML
22
42
0
28 Mar 2022
Sample Selection for Fair and Robust Training
Sample Selection for Fair and Robust Training
Yuji Roh
Kangwook Lee
Steven Euijong Whang
Changho Suh
21
61
0
27 Oct 2021
Clean or Annotate: How to Spend a Limited Data Collection Budget
Clean or Annotate: How to Spend a Limited Data Collection Budget
Derek Chen
Zhou Yu
Samuel R. Bowman
35
13
0
15 Oct 2021
Truth Discovery in Sequence Labels from Crowds
Truth Discovery in Sequence Labels from Crowds
Nasim Sabetpour
Adithya Kulkarni
Sihong Xie
Qi Li
36
16
0
09 Sep 2021
Co-learning: Learning from Noisy Labels with Self-supervision
Co-learning: Learning from Noisy Labels with Self-supervision
Cheng Tan
Jun-Xiong Xia
Lirong Wu
Stan Z. Li
NoLa
73
116
0
05 Aug 2021
Modality specific U-Net variants for biomedical image segmentation: A
  survey
Modality specific U-Net variants for biomedical image segmentation: A survey
Narinder Singh Punn
Sonali Agarwal
SSeg
29
144
0
09 Jul 2021
Learning from Multiple Annotators by Incorporating Instance Features
Learning from Multiple Annotators by Incorporating Instance Features
Jingzheng Li
Hailong Sun
Jiyi Li
Zhijun Chen
Renshuai Tao
Yufei Ge
NoLa
21
5
0
29 Jun 2021
Impact of individual rater style on deep learning uncertainty in medical
  imaging segmentation
Impact of individual rater style on deep learning uncertainty in medical imaging segmentation
Olivier Vincent
C. Gros
Julien Cohen-Adad
24
10
0
05 May 2021
DST: Data Selection and joint Training for Learning with Noisy Labels
DST: Data Selection and joint Training for Learning with Noisy Labels
Yi Wei
Xue Mei
Xin Liu
Pengxiang Xu
NoLa
21
3
0
01 Mar 2021
Improving Medical Image Classification with Label Noise Using
  Dual-uncertainty Estimation
Improving Medical Image Classification with Label Noise Using Dual-uncertainty Estimation
Lie Ju
Xin Wang
Lin Wang
Dwarikanath Mahapatra
Xin Zhao
Mehrtash Harandi
Tom Drummond
Tongliang Liu
Z. Ge
NoLa
OOD
30
22
0
28 Feb 2021
Leveraging Activity Recognition to Enable Protective Behavior Detection
  in Continuous Data
Leveraging Activity Recognition to Enable Protective Behavior Detection in Continuous Data
Chongyang Wang
Yuan Gao
Akhil Mathur
A. Williams
Nicholas D. Lane
N. Bianchi-Berthouze
24
34
0
03 Nov 2020
Learning Noise-Aware Encoder-Decoder from Noisy Labels by Alternating
  Back-Propagation for Saliency Detection
Learning Noise-Aware Encoder-Decoder from Noisy Labels by Alternating Back-Propagation for Saliency Detection
Jing Zhang
Jianwen Xie
Nick Barnes
NoLa
50
57
0
23 Jul 2020
Deep learning with noisy labels: exploring techniques and remedies in
  medical image analysis
Deep learning with noisy labels: exploring techniques and remedies in medical image analysis
Davood Karimi
Haoran Dou
Simon K. Warfield
Ali Gholipour
NoLa
13
535
0
05 Dec 2019
Confidence Calibration and Predictive Uncertainty Estimation for Deep
  Medical Image Segmentation
Confidence Calibration and Predictive Uncertainty Estimation for Deep Medical Image Segmentation
Alireza Mehrtash
W. Wells
C. Tempany
Purang Abolmaesumi
Tina Kapur
OOD
FedML
UQCV
24
262
0
29 Nov 2019
Confident Learning: Estimating Uncertainty in Dataset Labels
Confident Learning: Estimating Uncertainty in Dataset Labels
Curtis G. Northcutt
Lu Jiang
Isaac L. Chuang
NoLa
36
674
0
31 Oct 2019
A Survey on Deep Learning in Medical Image Analysis
A Survey on Deep Learning in Medical Image Analysis
G. Litjens
Thijs Kooi
B. Bejnordi
A. Setio
F. Ciompi
Mohsen Ghafoorian
Jeroen van der Laak
Bram van Ginneken
C. I. Sánchez
OOD
295
10,618
0
19 Feb 2017
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