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Supervision and Source Domain Impact on Representation Learning: A
  Histopathology Case Study

Supervision and Source Domain Impact on Representation Learning: A Histopathology Case Study

10 May 2020
Milad Sikaroudi
Amir Safarpoor
Benyamin Ghojogh
Sobhan Shafiei
Mark Crowley
H. R. Tizhoosh
    SSLOOD
ArXiv (abs)PDFHTML

Papers citing "Supervision and Source Domain Impact on Representation Learning: A Histopathology Case Study"

4 / 4 papers shown
Title
Attention-based Dynamic Subspace Learners for Medical Image Analysis
Attention-based Dynamic Subspace Learners for Medical Image Analysis
V. SukeshAdiga
Jose Dolz
H. Lombaert
51
1
0
18 Jun 2022
Learning to Predict RNA Sequence Expressions from Whole Slide Images
  with Applications for Search and Classification
Learning to Predict RNA Sequence Expressions from Whole Slide Images with Applications for Search and Classification
Amir Safarpoor
J. Hipp
H. R. Tizhoosh
MedIm
45
31
0
26 Mar 2022
Batch-Incremental Triplet Sampling for Training Triplet Networks Using
  Bayesian Updating Theorem
Batch-Incremental Triplet Sampling for Training Triplet Networks Using Bayesian Updating Theorem
Milad Sikaroudi
Benyamin Ghojogh
Fakhri Karray
Mark Crowley
H. R. Tizhoosh
32
3
0
10 Jul 2020
Offline versus Online Triplet Mining based on Extreme Distances of
  Histopathology Patches
Offline versus Online Triplet Mining based on Extreme Distances of Histopathology Patches
Milad Sikaroudi
Benyamin Ghojogh
Amir Safarpoor
Fakhri Karray
Mark Crowley
H. R. Tizhoosh
70
17
0
04 Jul 2020
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