1 code implementation • 1 Feb 2024 • Andres Pulido, Kyle Volle, Kristy Waters, Zachary I. Bell, Prashant Ganesh, Jane Shin
This neural network (NN)-based motion model serves as the prediction step in a particle filter for target state estimation and uncertainty quantification.
no code implementations • 21 Aug 2023 • Skylar E. Stolte, Kyle Volle, Aprinda Indahlastari, Alejandro Albizu, Adam J. Woods, Kevin Brink, Matthew Hale, Ruogu Fang
OOD data consists of test data that is significantly different from the model's training data.
1 code implementation • 10 Feb 2023 • Skylar E. Stolte, Kyle Volle, Aprinda Indahlastari, Alejandro Albizu, Adam J. Woods, Kevin Brink, Matthew Hale, Ruogu Fang
Deep learning has achieved the state-of-the-art performance across medical imaging tasks; however, model calibration is often not considered.
1 code implementation • 13 Sep 2022 • Skylar E. Stolte, Kyle Volle, Aprinda Indahlastari, Alejandro Albizu, Adam J. Woods, Kevin Brink, Matthew Hale, Ruogu Fang
Our experiments demonstrate that our DOMINO-calibrated deep neural networks outperform non-calibrated models and state-of-the-art morphometric methods in head image segmentation.
no code implementations • 1 Aug 2022 • J. Humberto Ramos, Jaejeong Shin, Kyle Volle, Paul Buzaud, Kevin Brink, Prashant Ganesh
In the absence of an absolute positioning system, such as GPS, autonomous vehicles are subject to accumulation of positional error which can interfere with reliable performance.