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Semi-supervised Learning using Adversarial Training with Good and Bad
  Samples

Semi-supervised Learning using Adversarial Training with Good and Bad Samples

18 October 2019
Wenyuan Li
Zichen Wang
Yuguang Yue
Jiayun Li
W. Speier
Mingyuan Zhou
C. Arnold
    GAN
ArXivPDFHTML

Papers citing "Semi-supervised Learning using Adversarial Training with Good and Bad Samples"

5 / 5 papers shown
Title
On the link between generative semi-supervised learning and generative
  open-set recognition
On the link between generative semi-supervised learning and generative open-set recognition
E. Engelbrecht
Johan A. du Preez
GAN
26
2
0
21 Mar 2023
Semi-supervised Bladder Tissue Classification in Multi-Domain Endoscopic
  Images
Semi-supervised Bladder Tissue Classification in Multi-Domain Endoscopic Images
Jorge F. Lazo
Benoit Rosa
M. Catellani
M. Fontana
F. Mistretta
G. Musi
O. de Cobelli
M. de Mathelin
Elena De Momi
MedIm
30
4
0
21 Dec 2022
Unlabeled Data Guided Semi-supervised Histopathology Image Segmentation
Unlabeled Data Guided Semi-supervised Histopathology Image Segmentation
Hongxiao Wang
Hao Zheng
Jianxu Chen
Lin Yang
Yizhe Zhang
Danny Chen
MedIm
28
4
0
17 Dec 2020
Mask-guided sample selection for Semi-Supervised Instance Segmentation
Mask-guided sample selection for Semi-Supervised Instance Segmentation
Míriam Bellver
Amaia Salvador
Jordi Torres
Xavier Giró-i-Nieto
ISeg
11
5
0
25 Aug 2020
Open-set learning with augmented categories by exploiting unlabelled
  data
Open-set learning with augmented categories by exploiting unlabelled data
E. Engelbrecht
J. D. Preez
41
0
0
04 Feb 2020
1