2022
DOI: 10.48550/arxiv.2208.03020
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Deep Bayesian Active-Learning-to-Rank for Endoscopic Image Data

Abstract: Automatic image-based disease severity estimation generally uses discrete (i.e., quantized) severity labels. Annotating discrete labels is often difficult due to the images with ambiguous severity. An easier alternative is to use relative annotation, which compares the severity level between image pairs. By using a learning-to-rank framework with relative annotation, we can train a neural network that estimates rank scores that are relative to severity levels. However, the relative annotation for all possible … Show more

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