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Adapting Self-Supervised Learning for Computational Pathology

Adapting Self-Supervised Learning for Computational Pathology

2 May 2024
Eric Zimmermann
Neil Tenenholtz
James Hall
George Shaikovski
Michal Zelechowski
Adam Casson
Fausto Milletari
Julian Viret
Eugene Vorontsov
Siqi Liu
Kristen Severson
    OOD
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Papers citing "Adapting Self-Supervised Learning for Computational Pathology"

4 / 4 papers shown
Title
DINOv2 Rocks Geological Image Analysis: Classification, Segmentation,
  and Interpretability
DINOv2 Rocks Geological Image Analysis: Classification, Segmentation, and Interpretability
Florent Brondolo
Samuel Beaussant
AI4CE
26
0
0
25 Jul 2024
Scale-MAE: A Scale-Aware Masked Autoencoder for Multiscale Geospatial
  Representation Learning
Scale-MAE: A Scale-Aware Masked Autoencoder for Multiscale Geospatial Representation Learning
Colorado Reed
Ritwik Gupta
Shufan Li
S. Brockman
Christopher Funk
Brian Clipp
Kurt Keutzer
Salvatore Candido
M. Uyttendaele
Trevor Darrell
121
169
0
30 Dec 2022
Masked Autoencoders Are Scalable Vision Learners
Masked Autoencoders Are Scalable Vision Learners
Kaiming He
Xinlei Chen
Saining Xie
Yanghao Li
Piotr Dollár
Ross B. Girshick
ViT
TPM
305
7,443
0
11 Nov 2021
Emerging Properties in Self-Supervised Vision Transformers
Emerging Properties in Self-Supervised Vision Transformers
Mathilde Caron
Hugo Touvron
Ishan Misra
Hervé Jégou
Julien Mairal
Piotr Bojanowski
Armand Joulin
317
5,785
0
29 Apr 2021
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