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Predicting breast tumor proliferation from whole-slide images: the TUPAC16 challenge


Jul 22, 2018
Mitko Veta, Yujing J. Heng, Nikolas Stathonikos, Babak Ehteshami Bejnordi, Francisco Beca, Thomas Wollmann, Karl Rohr, Manan A. Shah, Dayong Wang, Mikael Rousson, Martin Hedlund, David Tellez, Francesco Ciompi, Erwan Zerhouni, David Lanyi, Matheus Viana, Vassili Kovalev, Vitali Liauchuk, Hady Ahmady Phoulady, Talha Qaiser, Simon Graham, Nasir Rajpoot, Erik Sjöblom, Jesper Molin, Kyunghyun Paeng, Sangheum Hwang, Sunggyun Park, Zhipeng Jia, Eric I-Chao Chang, Yan Xu, Andrew H. Beck, Paul J. van Diest, Josien P. W. Pluim

* Overview paper of the TUPAC16 challenge: http://tupac.tue-image.nl/ 

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A Unified Framework for Tumor Proliferation Score Prediction in Breast Histopathology


Aug 11, 2017
Kyunghyun Paeng, Sangheum Hwang, Sunggyun Park, Minsoo Kim

* Accepted to the 3rd Workshop on Deep Learning in Medical Image Analysis (DLMIA 2017), MICCAI 2017 

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Accurate Lung Segmentation via Network-Wise Training of Convolutional Networks


Aug 02, 2017
Sangheum Hwang, Sunggyun Park

* Accepted to the 3rd Workshop on Deep Learning in Medical Image Analysis (DLMIA 2017), MICCAI 2017 

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Action-Driven Object Detection with Top-Down Visual Attentions


Dec 20, 2016
Donggeun Yoo, Sunggyun Park, Kyunghyun Paeng, Joon-Young Lee, In So Kweon


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Pixel-Level Domain Transfer


Nov 28, 2016
Donggeun Yoo, Namil Kim, Sunggyun Park, Anthony S. Paek, In So Kweon

* Published in ECCV 2016. Code and dataset available at dgyoo.github.io 

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AttentionNet: Aggregating Weak Directions for Accurate Object Detection


Sep 26, 2015
Donggeun Yoo, Sunggyun Park, Joon-Young Lee, Anthony S. Paek, In So Kweon

* To appear in ICCV 2015 

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Fisher Kernel for Deep Neural Activations


Dec 19, 2014
Donggeun Yoo, Sunggyun Park, Joon-Young Lee, In So Kweon


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