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 & AI!
We've feely open-sourced our new method for improving segmentation data and published a paper on the research behind it. https://arxiv.org/abs/2307.05080
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 & AI!
We've feely open-sourced our new method for improving segmentation data and published a paper on the research behind it. https://arxiv.org/abs/2307.05080