Uncertainty in AI(3)
* Bayesian Inference in Model-Based Machine Vision
Uncertainty22
* *Uncertainty Quantification for Computer Vision
* Localization Uncertainty Estimation for Anchor-free Object Detection
* Uncertainty Quantification Using Query-based Object Detectors
* Unsupervised Joint Image Transfer and Uncertainty Quantification Using Patch Invariant Networks
* Variational Depth Networks: Uncertainty-aware Monocular Self-supervised Depth Estimation
Uncertainty23
* *Uncertainty Estimation for Computer Vision
* Adversarial Attacks Against Uncertainty Quantification
* Biased Class disagreement: detection of out of distribution instances by using differently biased semantic segmentation models
* Calibrated Out-of-Distribution Detection with a Generic Representation
* DELO: Deep Evidential LiDAR Odometry using Partial Optimal Transport
* Distance Matters For Improving Performance Estimation Under Covariate Shift
* Dual-level Interaction for Domain Adaptive Semantic Segmentation
* Exploring Inlier and Outlier Specification for Improved Medical OOD Detection
* Far Away in the Deep Space: Dense Nearest-Neighbor-Based Out-of-Distribution Detection
* Gaussian Latent Representations for Uncertainty Estimation using Mahalanobis Distance in Deep Classifiers
* Identifying Out-of-Domain Objects with Dirichlet Deep Neural Networks
* Probabilistic MIMO U-Net: Efficient and Accurate Uncertainty Estimation for Pixel-wise Regression
* Robust Semantic Segmentation UNCV2023 Challenge Results, The
* Simple and Explainable Method for Uncertainty Estimation using Attribute Prototype Networks, A
* UncLe-SLAM: Uncertainty Learning for Dense Neural SLAM
* Unsupervised Confidence Approximation: Trustworthy Learning from Noisy Labelled Data
16 for Uncertainty23