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Deep Learning with Permutation-invariant Operator for Multi-instance
  Histopathology Classification
v1v2 (latest)

Deep Learning with Permutation-invariant Operator for Multi-instance Histopathology Classification

1 December 2017
Jakub M. Tomczak
Maximilian Ilse
Max Welling
    MedIm
ArXiv (abs)PDFHTML

Papers citing "Deep Learning with Permutation-invariant Operator for Multi-instance Histopathology Classification"

7 / 7 papers shown
Title
Learning Time-Invariant Representations for Individual Neurons from
  Population Dynamics
Learning Time-Invariant Representations for Individual Neurons from Population Dynamics
Lu Mi
Trung Le
Tianxing He
Eli Shlizerman
U. Sümbül
83
5
0
03 Nov 2023
Pay Attention with Focus: A Novel Learning Scheme for Classification of
  Whole Slide Images
Pay Attention with Focus: A Novel Learning Scheme for Classification of Whole Slide Images
Shivam Kalra
Mohammed Adnan
S. Hemati
Taher Dehkharghanian
Shahryar Rahnamayan
Hamid Tizhoosh
74
13
0
11 Jun 2021
A Multi-resolution Model for Histopathology Image Classification and
  Localization with Multiple Instance Learning
A Multi-resolution Model for Histopathology Image Classification and Localization with Multiple Instance Learning
Jiayun Li
Wenyuan Li
Anthony Sisk
Huihui Ye
W. D. Wallace
W. Speier
C. Arnold
67
111
0
05 Nov 2020
Representation Learning of Histopathology Images using Graph Neural
  Networks
Representation Learning of Histopathology Images using Graph Neural Networks
Mohammed Adnan
Shivam Kalra
Hamid R. Tizhoosh
OOD
49
100
0
16 Apr 2020
Learning Permutation Invariant Representations using Memory Networks
Learning Permutation Invariant Representations using Memory Networks
Shivam Kalra
Mohammed Adnan
Graham W. Taylor
Hamid Tizhoosh
71
24
0
18 Nov 2019
Monte-Carlo Sampling applied to Multiple Instance Learning for
  Histological Image Classification
Monte-Carlo Sampling applied to Multiple Instance Learning for Histological Image Classification
Marc Combalia
João Paulo Papa
81
83
0
30 Dec 2018
Not-so-supervised: a survey of semi-supervised, multi-instance, and
  transfer learning in medical image analysis
Not-so-supervised: a survey of semi-supervised, multi-instance, and transfer learning in medical image analysis
Veronika Cheplygina
Marleen de Bruijne
J. Pluim
86
761
0
17 Apr 2018
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