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Intrapapillary Capillary Loop Classification in Magnification Endoscopy: Open Dataset and Baseline Methodology

Intrapapillary Capillary Loop Classification in Magnification Endoscopy: Open Dataset and Baseline Methodology

Luis C. Garcia-Peraza-Herrera
M. Everson
Laurence B. Lovat
Hsiu‐Po Wang
Wen-Lun Wang
R. Haidry
Danail Stoyanov
Sebastien Ourselin
Tom Vercauteren
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Papers citing "Intrapapillary Capillary Loop Classification in Magnification Endoscopy: Open Dataset and Baseline Methodology"

4 / 4 papers shown
Title
Interpretable Fully Convolutional Classification of Intrapapillary Capillary Loops for Real-Time Detection of Early Squamous Neoplasia
Interpretable Fully Convolutional Classification of Intrapapillary Capillary Loops for Real-Time Detection of Early Squamous Neoplasia
Luis C. Garcéa-Peraza-Herrera
M. Everson
Wenqi Li
I. Luengo
L. Berger
...
Wen-Lun Wang
R. Haidry
Danail Stoyanov
Tom Vercauteren
Sebastien Ourselin
23
9
0
02 May 2018
Methods for Interpreting and Understanding Deep Neural Networks
Methods for Interpreting and Understanding Deep Neural Networks
G. Montavon
Wojciech Samek
K. Müller
FaML
293
2,266
0
24 Jun 2017
Learning Deep Features for Discriminative Localization
Learning Deep Features for Discriminative Localization
Bolei Zhou
A. Khosla
Àgata Lapedriza
A. Oliva
Antonio Torralba
SSLSSegFAtt
250
9,326
0
14 Dec 2015
Deep Residual Learning for Image Recognition
Deep Residual Learning for Image Recognition
Kaiming He
Xinming Zhang
Shaoqing Ren
Jian Sun
MedIm
2.2K
194,322
0
10 Dec 2015

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