Learning with Noisy Labels for Human Fall Events Classification: Joint Cooperative Training with Trinity Networks

27 September 2023

Papers citing "Learning with Noisy Labels for Human Fall Events Classification: Joint Cooperative Training with Trinity Networks"

8 / 8 papers shown

Title
Combating noisy labels by agreement: A joint training method with co-regularization Hongxin Wei Lei Feng Xiangyu Chen Bo An NoLa 345 514 0 05 Mar 2020
Confident Learning: Estimating Uncertainty in Dataset Labels Curtis G. Northcutt Lu Jiang Isaac L. Chuang NoLa 149 692 0 31 Oct 2019
Probabilistic End-to-end Noise Correction for Learning with Noisy Labels Kun Yi Jianxin Wu NoLa 68 417 0 19 Mar 2019
How does Disagreement Help Generalization against Label Corruption? Xingrui Yu Bo Han Jiangchao Yao Gang Niu Ivor W. Tsang Masashi Sugiyama NoLa 65 783 0 14 Jan 2019
Learning to Reweight Examples for Robust Deep Learning Mengye Ren Wenyuan Zeng Binh Yang R. Urtasun OOD NoLa 146 1,426 0 24 Mar 2018
MentorNet: Learning Data-Driven Curriculum for Very Deep Neural Networks on Corrupted Labels Lu Jiang Zhengyuan Zhou Thomas Leung Li Li Li Fei-Fei NoLa 98 1,453 0 14 Dec 2017
A Closer Look at Memorization in Deep Networks Devansh Arpit Stanislaw Jastrzebski Nicolas Ballas David M. Krueger Emmanuel Bengio ... Tegan Maharaj Asja Fischer Aaron Courville Yoshua Bengio Simon Lacoste-Julien TDI 125 1,818 0 16 Jun 2017
RMPE: Regional Multi-person Pose Estimation Haoshu Fang Shuqin Xie Yu-Wing Tai Cewu Lu 3DH 123 1,586 0 01 Dec 2016