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

Zichen Wang

Mingyuan Zhou

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 E. Engelbrecht Johan A. du Preez GAN 29 2 0 21 Mar 2023
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 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 Míriam Bellver Amaia Salvador Jordi Torres Xavier Giró-i-Nieto ISeg 16 5 0 25 Aug 2020
Open-set learning with augmented categories by exploiting unlabelled data E. Engelbrecht J. D. Preez 41 0 0 04 Feb 2020