← Search

Rainer Kiko

2 accepted papers

2022

A Data-Centric Approach for Improving Ambiguous Labels with Combined Semi-Supervised Classification and Clustering

ECCV 2022poster

"Consistently high data quality is essential for the development of novel loss functions and architectures in the field of deep learning. The existence of such data and labels is usually presumed, while acquiring high-quality datasets is still a major issue in many cases. Subjective annotations by a…

2022

Is one annotation enough? - A data-centric image classification benchmark for noisy and ambiguous label estimation

NeurIPS 2022accept

High-quality data is necessary for modern machine learning. However, the acquisition of such data is difficult due to noisy and ambiguous annotations of humans. The aggregation of such annotations to determine the label of an image leads to a lower data quality. We propose a data-centric image class…