11 citations · 11 across the 2 of their papers we have counts for
2 papers
cs.CV2022★ 11 cited
Is one annotation enough? A data-centric image classification benchmark for noisy and ambiguous label estimation
Lars Schmarje, Vasco Grossmann, Claudius Zelenka +8
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…
cs.CV2021
A data-centric approach for improving ambiguous labels with combined semi-supervised classification and clustering
Lars Schmarje, Monty Santarossa, Simon-Martin Schröder +5
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 us…