EuroVis · 2020
Classifier-Guided Visual Correction of Noisy Labels for Image Classification Tasks
Alex Bäuerle, Heiko Neumann, and Timo Ropinski
Abstract
Training data plays an essential role in modern applications of machine learning. In this project, we provide means to visually guide users towards potential errors in such datasets. Our guidance, which is built on common labeling error types we propose, can be plugged into any classification pipeline.