Scaled conformal prediction using aleatoric uncertainty estimates and class-wise calibration produces sharper valid prediction intervals for object detection than unscaled variants, with up to 19% higher IoU and 39% lower interval scores on driving datasets.
Making deep learning models clinically useful --- improving diagnostic confidence in inherited retinal disease with conformal prediction , booktitle =
1 Pith paper cite this work. Polarity classification is still indexing.
1
Pith paper citing it
citation-role summary
background 1
citation-polarity summary
fields
cs.CV 1years
2026 1verdicts
UNVERDICTED 1roles
background 1polarities
unclear 1representative citing papers
citing papers explorer
-
Probabilistic Object Detection with Conformal Prediction
Scaled conformal prediction using aleatoric uncertainty estimates and class-wise calibration produces sharper valid prediction intervals for object detection than unscaled variants, with up to 19% higher IoU and 39% lower interval scores on driving datasets.