Essays about: "aleatoric uncertainty estimation"

Found 3 essays containing the words aleatoric uncertainty estimation.

  1. 1. Uncertainty Estimation in Radiation Dose Prediction U-Net

    University essay from KTH/Skolan för elektroteknik och datavetenskap (EECS)

    Author : Frida Skarf; [2023]
    Keywords : Radiation dose prediction models; U-net; quantile regression; Monte Carlo Dropout; epistemic uncertainty estimation; aleatoric uncertainty estimation; Stråldospredicerande modeller; U-net; kvantilregression; Monte Carlo Dropout; epistemisk osäkerhetsskattning; aletorisk osäkerhetsskattning;

    Abstract : The ability to quantify uncertainties associated with neural network predictions is crucial when they are relied upon in decision-making processes, especially in safety-critical applications like radiation therapy. In this paper, a single-model estimator of both epistemic and aleatoric uncertainties in a regression 3D U-net used for radiation dose prediction is presented. READ MORE

  2. 2. Uncertainty Estimation in Volumetric Image Segmentation

    University essay from KTH/Skolan för elektroteknik och datavetenskap (EECS)

    Author : Donggyun Park; [2023]
    Keywords : Uncertainty Estimation; Uncertainty Quantification UQ ; Volumetric Image Segmentation; 3D U-Net; test-time data augmentation; Deep ensemble;

    Abstract : The performance of deep neural networks and estimations of their robustness has been rapidly developed. In contrast, despite the broad usage of deep convolutional neural networks (CNNs)[1] for medical image segmentation, research on their uncertainty estimations is being far less conducted. READ MORE

  3. 3. Real-time Uncertainty Estimation for Semantic Segmentation : Improving Uncertainty Estimates with Temperature Scaling and Predicted Dirichlet Distributions

    University essay from KTH/Skolan för elektroteknik och datavetenskap (EECS)

    Author : Lukas Grannas; [2020]
    Keywords : ;

    Abstract : This degree project examined different aspects of real-time uncertainty estimation for semantic segmentation deep learning networks in an autonomous driving setting. Two main tracks were taken. READ MORE