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Transforming medical imaging with Transformers? A comparative review of key properties, current progresses, and future perspectives
2 June 2022
Jun Li
Junyu Chen
Yucheng Tang
Ce Wang
Bennett A. Landman
S. K. Zhou
ViT
OOD
MedIm
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Papers citing
"Transforming medical imaging with Transformers? A comparative review of key properties, current progresses, and future perspectives"
11 / 161 papers shown
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DeepLab: Semantic Image Segmentation with Deep Convolutional Nets, Atrous Convolution, and Fully Connected CRFs
Liang-Chieh Chen
George Papandreou
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Kevin Patrick Murphy
Alan Yuille
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Multi-Scale Context Aggregation by Dilated Convolutions
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V. Koltun
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Dropout as a Bayesian Approximation: Representing Model Uncertainty in Deep Learning
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Max Jaderberg
Karen Simonyan
Andrew Zisserman
Koray Kavukcuoglu
316
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05 Jun 2015
Show, Attend and Tell: Neural Image Caption Generation with Visual Attention
Ke Xu
Jimmy Ba
Ryan Kiros
Kyunghyun Cho
Aaron Courville
Ruslan Salakhutdinov
R. Zemel
Yoshua Bengio
DiffM
350
10,083
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10 Feb 2015
Neural Machine Translation by Jointly Learning to Align and Translate
Dzmitry Bahdanau
Kyunghyun Cho
Yoshua Bengio
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578
27,338
0
01 Sep 2014
A New 2.5D Representation for Lymph Node Detection using Random Sets of Deep Convolutional Neural Network Observations
H. Roth
Le Lu
Ari Seff
Kevin M. Cherry
Joanne Hoffman
Shijun Wang
Jiamin Liu
E. Turkbey
Ronald M. Summers
MedIm
80
544
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06 Jun 2014
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