51 citations · 98 across the 16 of their papers we have counts for
Showing 2023 · cs.LGShow all
3 papers · 2 filters
cs.LG2023★ 3 cited
Estimating label quality and errors in semantic segmentation data via any model
Vedang Lad, Jonas Mueller
The labor-intensive annotation process of semantic segmentation datasets is often prone to errors, since humans struggle to label every pixel correctly. We study algorithms to auto…
cs.LG2023
Detecting Dataset Drift and Non-IID Sampling via k-Nearest Neighbors
Jesse Cummings, Elías Snorrason, Jonas Mueller
We present a straightforward statistical test to detect certain violations of the assumption that the data are Independent and Identically Distributed (IID). The specific form of v…
cs.LG2023★ 1 cited
ActiveLab: Active Learning with Re-Labeling by Multiple Annotators
Hui Wen Goh, Jonas Mueller
In real-world data labeling applications, annotators often provide imperfect labels. It is thus common to employ multiple annotators to label data with some overlap between their e…