Identifying Incorrect Annotations in Multi-Label Classification Data

25 November 2022

Papers citing "Identifying Incorrect Annotations in Multi-Label Classification Data"

8 / 8 papers shown

Title
A quest through interconnected datasets: lessons from highly-cited ICASSP papers Cynthia C. S. Liem Doğa Taşcılar Andrew M. Demetriou 25 0 0 19 Sep 2024
An Empirical Study of Automated Mislabel Detection in Real World Vision Datasets Maya Srikanth Jeremy Irvin Brian Wesley Hill Felipe Godoy Ishan Sabane Andrew Y. Ng 35 2 0 02 Dec 2023
ObjectLab: Automated Diagnosis of Mislabeled Images in Object Detection Data Ulyana Tkachenko Aditya Thyagarajan Jonas W. Mueller 17 4 0 02 Sep 2023
Estimating label quality and errors in semantic segmentation data via any model Vedang Lad Jonas W. Mueller UQCV 40 5 0 11 Jul 2023
Positive Label Is All You Need for Multi-Label Classification Zhixiang Yuan Kai Zhang Tao Huang NoLa 13 5 0 28 Jun 2023
Detecting Errors in a Numerical Response via any Regression Model Hang Zhou Jonas W. Mueller Mayank Kumar Jane-ling Wang Jing-Sheng Lei 31 0 0 26 May 2023
Identifying Label Errors in Object Detection Datasets by Loss Inspection Marius Schubert Tobias Riedlinger Karsten Kahl Daniel Kröll S. Schoenen Sinisa Segvic Matthias Rottmann NoLa 32 6 0 13 Mar 2023
Combating noisy labels in object detection datasets K. Chachula Jakub Lyskawa Bartlomiej Olber Piotr Fratczak A. Popowicz Krystian Radlak NoLa 26 4 0 25 Nov 2022