Estimating label quality and errors in semantic segmentation data via any model · HackerPapers discussionshttps://hackerpaper.kaipfister.de/p/2307.05080/Collected HN comments and submissions linking this paper.enMon, 02 Nov 2026 11:16:22 GMTEstimating label quality and errors in semantic segmentation data via any model — mentioned by cmauck10https://news.ycombinator.com/item?id=38115278urn:hackerpapers:mention:2307.05080:38115278Thu, 02 Nov 2023 15:51:55 GMT<p>Would you trust medical AI that’s been trained on pathology/radiology images where tumors/injuries were overlooked by data annotators or otherwise mislabeled? Most image segmentation datasets today contain tons of errors because it is painstaking to annotate every pixel. We have added semantic segmentation to automatically catch annotation errors in image segmentation datasets, before they harm your models! Quickly use cleanlab open source to detect bad data and fix it before training/evaluating your segmentation models. This is the easiest way to increase the reliability of your data &amp; AI!…</p><p><a href="https://hackerpaper.kaipfister.de/p/2307.05080/">Paper and discussion history</a>. A mention is not an endorsement.</p>cs.LG