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Faster Semantic Segmentation with Machine Learning-Assisted Workflows cover
Engineering

Faster Semantic Segmentation with Machine Learning-Assisted Workflows

This blog post introduces Autosegment, an ML-powered tool that can segment instances within a human-provided box. We have found that we can delegate high-level reasoning to Taskers (the labelers on our platform) and leave basic semantic segmentation to an ML model. This division of labor allowed us to build a 30% faster generalizable and accurate ML labeling tool through a conceptually simple implementation.

Nov 9th, 2021

Scale AI and Research Partner MIT Media Lab Analyze Bias in Dermatological Datasets to Improve Diagnoses cover
Company

Scale AI and Research Partner MIT Media Lab Analyze Bias in Dermatological Datasets to Improve Diagnoses

Recent studies demonstrate computer vision models can serve as a useful decision support tool in healthcare but darker skin is underrepresented in datasets. The lack of consideration has been shown to lead neural networks to produce large accuracy disparities. This research sought to determine if adding Fitzpatrick labels would allow researchers to assess algorithmic fairness to ensure better performance.

Jun 23rd, 2021