Deep Bayesian Active-Learning-to-Rank for Endoscopic Image Data. (arXiv:2208.03020v1 [cs.CV])

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 pairs is prohibitive,
and therefore, appropriate sample pair …

arxiv bayesian cv data image learning learning-to-rank