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The Master Guide to Data Curation and Auto Curation for Computer Vision
In this dedicated guide, you’ll learn about industry-standard methods in data curation for computer vision model development. Get a step-by-step understanding of how raw data is prepared through preprocessing, discover which tools have become essential to precise data curation efforts, as well as what automating that process looks like through Superb AI’s own platform and DataOps features to modernize the conventions of the data curation workflow.
How to Improve Data Labeling Efficiency with Auto-Labeling, Uncertainty Estimates, and Active Learning
In this whitepaper, we dive into the machine learning theory and techniques that were developed to evaluate our auto-labeling AI. More specifically, how the platform estimates the uncertainty of auto-labeled annotations and applies it to active learning. This whitepaper will help you measure and evaluate how much you can trust the model output when utilizing auto labeling for data annotation.