Combining MixMatch and Active Learning for Better Accuracy with Fewer Labels

2 December 2019

Papers citing "Combining MixMatch and Active Learning for Better Accuracy with Fewer Labels"

11 / 11 papers shown

Title
Monocular 3D Object Detection with LiDAR Guided Semi Supervised Active Learning A. Hekimoglu Michael Schmidt Alvaro Marcos-Ramiro 3DPC 43 10 0 17 Jul 2023
Training Ensembles with Inliers and Outliers for Semi-supervised Active Learning Vladan Stojnić Zakaria Laskar Giorgos Tolias 42 0 0 07 Jul 2023
An Empirical Study on the Efficacy of Deep Active Learning for Image Classification Yu Li Mu-Hwa Chen Yannan Liu Daojing He Qiang Xu 42 9 0 30 Nov 2022
Consistency-Based Semi-supervised Evidential Active Learning for Diagnostic Radiograph Classification Shafa Balaram C. Nguyen Ashraf Kassim Pavitra Krishnaswamy EDL 23 11 0 05 Sep 2022
Exploiting Diversity of Unlabeled Data for Label-Efficient Semi-Supervised Active Learning F. Buchert Nassir Navab Seong Tae Kim 33 6 0 25 Jul 2022
BoostMIS: Boosting Medical Image Semi-supervised Learning with Adaptive Pseudo Labeling and Informative Active Annotation Wenqiao Zhang Lei Zhu James Hallinan A. Makmur Shengyu Zhang Qingpeng Cai Beng Chin Ooi 35 80 0 04 Mar 2022
Data Summarization via Bilevel Optimization Zalan Borsos Mojmír Mutný Marco Tagliasacchi Andreas Krause 35 8 0 26 Sep 2021
A Neural Pre-Conditioning Active Learning Algorithm to Reduce Label Complexity Seo Taek Kong Soomin Jeon Dongbin Na Jaewon Lee Honglak Lee Kyu-Hwan Jung 23 6 0 08 Apr 2021
Semi-supervised Batch Active Learning via Bilevel Optimization Zalan Borsos Marco Tagliasacchi Andreas Krause 39 23 0 19 Oct 2020
Consistency-based Semi-supervised Active Learning: Towards Minimizing Labeling Cost M. Gao Zizhao Zhang Guo-Ding Yu Sercan O. Arik L. Davis Tomas Pfister 168 196 0 16 Oct 2019
Mean teachers are better role models: Weight-averaged consistency targets improve semi-supervised deep learning results Antti Tarvainen Harri Valpola OOD MoMe 273 1,275 0 06 Mar 2017