Výsledky vyhledávání - "Noack, Benjamin"

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An Event-Based Approach for the Conservative Compression of Covariance Matrices

Autor: Funk, Christopher, Noack, Benjamin

This work introduces a flexible and versatile method for the data-efficient yet conservative transmission of covariance matrices, where a matrix element is only transmitted if a so-called triggering condition is satisfied for the element. Here, trigg

Externí odkaz: http://arxiv.org/abs/2403.05977

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Exploiting Structure for Optimal Multi-Agent Bayesian Decentralized Estimation

Autor: Funk, Christopher, Dagan, Ofer, Noack, Benjamin, Ahmed, Nisar R.

A key challenge in Bayesian decentralized data fusion is the `rumor propagation' or `double counting' phenomenon, where previously sent data circulates back to its sender. It is often addressed by approximate methods like covariance intersection (CI)

Externí odkaz: http://arxiv.org/abs/2307.10594

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Discriminative Feature Learning through Feature Distance Loss

Autor: Schlagenhauf, Tobias, Lin, Yiwen, Noack, Benjamin

Ensembles of Convolutional neural networks have shown remarkable results in learning discriminative semantic features for image classification tasks. Though, the models in the ensemble often concentrate on similar regions in images. This work propose

Externí odkaz: http://arxiv.org/abs/2205.11606

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Improved Pose Graph Optimization for Planar Motions Using Riemannian Geometry on the Manifold of Dual Quaternions

Autor: Li, Kailai, Cox, Johannes, Noack, Benjamin, Hanebeck, Uwe D.

We present a novel Riemannian approach for planar pose graph optimization problems. By formulating the cost function based on the Riemannian metric on the manifold of dual quaternions representing planar motions, the nonlinear structure of the SE(2)

Externí odkaz: http://arxiv.org/abs/1907.13566

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