Learning from Crowds with Sparse and Imbalanced Annotations

11 July 2021

Papers citing "Learning from Crowds with Sparse and Imbalanced Annotations"

6 / 6 papers shown

Title
The Majority Vote Paradigm Shift: When Popular Meets Optimal Antonio Purificato Maria Sofia Bucarelli Anil Kumar Nelakanti Andrea Bacciu Fabrizio Silvestri Amin Mantrach 68 0 0 18 Feb 2025
Unlocking the Power of Open Set : A New Perspective for Open-Set Noisy Label Learning Wenhai Wan Xinrui Wang Ming-Kun Xie Shao-Yuan Li Sheng-Jun Huang Songcan Chen 25 8 0 07 May 2023
In Defense of Pseudo-Labeling: An Uncertainty-Aware Pseudo-label Selection Framework for Semi-Supervised Learning Mamshad Nayeem Rizve Kevin Duarte Y. S. Rawat M. Shah 206 508 0 15 Jan 2021
BBN: Bilateral-Branch Network with Cumulative Learning for Long-Tailed Visual Recognition Boyan Zhou Quan Cui Xiu-Shen Wei Zhao-Min Chen 243 782 0 05 Dec 2019
Mean teachers are better role models: Weight-averaged consistency targets improve semi-supervised deep learning results Antti Tarvainen Harri Valpola OOD MoMe 244 1,275 0 06 Mar 2017
Dynamic Bayesian Combination of Multiple Imperfect Classifiers Edwin Simpson Stephen J. Roberts Ioannis Psorakis Arfon M. Smith 50 144 0 08 Jun 2012