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Learning from Thresholds: Fully Automated Classification of Tumor
  Infiltrating Lymphocytes for Multiple Cancer Types

Learning from Thresholds: Fully Automated Classification of Tumor Infiltrating Lymphocytes for Multiple Cancer Types

9 July 2019
Shahira Abousamra
L. Hou
Rajarsi R. Gupta
Chao Chen
Dimitris Samaras
Tahsin M. Kurc
R. Batiste
Tianhao Zhao
S. Kenneth
Joel H. Saltz
ArXivPDFHTML

Papers citing "Learning from Thresholds: Fully Automated Classification of Tumor Infiltrating Lymphocytes for Multiple Cancer Types"

3 / 3 papers shown
Title
Sparse Autoencoder for Unsupervised Nucleus Detection and Representation
  in Histopathology Images
Sparse Autoencoder for Unsupervised Nucleus Detection and Representation in Histopathology Images
L. Hou
Vu Nguyen
Dimitris Samaras
Tahsin M. Kurc
Yi Gao
Tianhao Zhao
Joel H. Saltz
MedIm
46
143
0
03 Apr 2017
Inception-v4, Inception-ResNet and the Impact of Residual Connections on
  Learning
Inception-v4, Inception-ResNet and the Impact of Residual Connections on Learning
Christian Szegedy
Sergey Ioffe
Vincent Vanhoucke
Alexander A. Alemi
265
14,196
0
23 Feb 2016
Very Deep Convolutional Networks for Large-Scale Image Recognition
Very Deep Convolutional Networks for Large-Scale Image Recognition
Karen Simonyan
Andrew Zisserman
FAtt
MDE
761
99,991
0
04 Sep 2014
1