Furthermore, an uncertainty quantification module is embedded to improve model interpretability and reliability, addressing concerns regarding AI-based medical decision-making.Experimental evaluations ...

Abstract: We present an efficient method for uncertainty quantification in 3D magnetotelluric (MT) inversions based on variational inference principles and the variational autoencoder (VAE) framework.

Abstract: Object detection is a fundamental task in computer vision, consisting of both classification and localization tasks. Previous works mostly perform classification and localization with shared ...

In summary, the proposed LTHRNet model demonstrates high accuracy and strong robustness in pineapple keypoint detection and pose estimation, providing reliable keypoint localization and ... methods ...

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Master's Thesis project on using machine learning as a part of a SHM assesment on a damaged, post-tensioned bridge.