59 citations · 61 across the 3 of their papers we have counts for
3 papers
Scaling Novel Object Detection with Weakly Supervised Detection Transformers
Tyler LaBonte, Yale Song, Xin Wang +2
A critical object detection task is finetuning an existing model to detect novel objects, but the standard workflow requires bounding box annotations which are time-consuming and e…
Quantifying the unknown impact of segmentation uncertainty on image-based simulations
Michael C. Krygier, Tyler LaBonte, Carianne Martinez +5
Image-based simulation, the use of 3D images to calculate physical quantities, fundamentally relies on image segmentation to create the computational geometry. However, this proces…
We Know Where We Don't Know: 3D Bayesian CNNs for Credible Geometric Uncertainty
Tyler LaBonte, Carianne Martinez, Scott A. Roberts
Deep learning has been successfully applied to the segmentation of 3D Computed Tomography (CT) scans. Establishing the credibility of these segmentations requires uncertainty quant…