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Benjamin Noack
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- affiliation: Karlsruhe Institute of Technology, ISAS, Germany
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2020 – today
- 2024
- [c75]Christopher Funk, Benjamin Noack:
Conservative Compression of Information Matrices using Event-Triggering and Robust Optimization. FUSION 2024: 1-8 - [c74]Eva Julia Schmitt, Benjamin Noack:
Event-based Multisensor Fusion with Correlated Estimates. FUSION 2024: 1-8 - [c73]Fabio Broghammer, Thomas Wiedemann, Siwei Zhang, Benjamin Noack:
Simultaneous Gas Exploration and Network Localization with Robotic Swarms. ICASSP Workshops 2024: 169-173 - [c72]Hafez Kader, Robin Ströbel, Alexander Puchta, Jürgen Fleischer, Benjamin Noack, Myra Spiliopoulou:
Feature Ranking for the Prediction of Energy Consumption on CNC Machining Processes. MFI 2024: 1-7 - [c71]Eva Julia Schmitt, Benjamin Noack:
Consistent Stochastic Event-based Estimation Under Packet Losses Using Low-Cost Sensors. MFI 2024: 1-7 - [i4]Christopher Funk, Benjamin Noack:
An Event-Based Approach for the Conservative Compression of Covariance Matrices. CoRR abs/2403.05977 (2024) - 2023
- [j16]Johannes Westermann
, Jana Mayer, Janko Petereit
Receding Horizon Cost-Aware Adaptive Sampling for Environmental Monitoring. IEEE Control. Syst. Lett. 7: 1069-1074 (2023) - [j15]Tobias Schlagenhauf
Discriminative feature learning through feature distance loss. Mach. Vis. Appl. 34(2): 25 (2023) - [j14]Marko Ristic
Distributed Range-Only Localization That Preserves Sensor and Navigator Privacies. IEEE Trans. Autom. Control. 68(12): 7151-7163 (2023) - [c70]Christopher Funk
Graduated Moving Window Optimization as a Flexible Framework for Multi-Object Tracking. ACC 2023: 4864-4870 - [c69]Anne Rother
Productive teaming under uncertainty: when a human and a machine classify objects together. ARSO 2023: 9-14 - [c68]Christopher Funk
Conservative Data Reduction for Covariance Matrices Using Elementwise Event Triggers. FUSION 2023: 1-6 - [c67]Jana Mayer, Vesa Klumpp, Jonas Hillenbrand, Benjamin Noack:
Statistical Approach for Preload Monitoring of Ball Screw Drives. SENSORS 2023: 1-4 - [i3]Christopher Funk, Ofer Dagan, Benjamin Noack, Nisar R. Ahmed:
Exploiting Structure for Optimal Multi-Agent Bayesian Decentralized Estimation. CoRR abs/2307.10594 (2023) - 2022
- [j13]Marko Ristic
Cryptographically Privileged State Estimation With Gaussian Keystreams. IEEE Control. Syst. Lett. 6: 602-607 (2022) - [c66]Marko Ristic, Benjamin Noack:
Privileged Estimate Fusion With Correlated Gaussian Keystreams. CDC 2022: 7732-7739 - [c65]Benjamin Noack, Clemens Öhl, Uwe D. Hanebeck:
Event-Based Kalman Filtering Exploiting Correlated Trigger Information. FUSION 2022: 1-8 - [c64]Marko Ristic, Benjamin Noack:
Encrypted Fast Covariance Intersection Without Leaking Fusion Weights. MFI 2022: 1-6 - [i2]Tobias Schlagenhauf, Yiwen Lin, Benjamin Noack:
Discriminative Feature Learning through Feature Distance Loss. CoRR abs/2205.11606 (2022) - 2021
- [j12]Marko Ristic, Benjamin Noack, Uwe D. Hanebeck:
Secure Fast Covariance Intersection Using Partially Homomorphic and Order Revealing Encryption Schemes. IEEE Control. Syst. Lett. 5(1): 217-222 (2021) - [j11]Christopher Funk
Conservative Quantization of Covariance Matrices with Applications to Decentralized Information Fusion. Sensors 21(9): 3059 (2021) - [j10]Georg Maier
Experimental Evaluation of a Novel Sensor-Based Sorting Approach Featuring Predictive Real-Time Multiobject Tracking. IEEE Trans. Ind. Electron. 68(2): 1548-1559 (2021) - [c63]Haibin Zhao
Kalman Filtered Compressive Sensing Using Pseudo-Measurements. MFI 2021: 1-8 - 2020
- [j9]Florian Pfaff, Christoph Pieper, Georg Maier, Benjamin Noack, Robin Gruna, Harald Kruggel-Emden
Predictive tracking with improved motion models for optical belt sorting. Autom. 68(4): 239-255 (2020) - [j8]Georg Maier, Florian Pfaff, Andrea Bittner, Robin Gruna, Benjamin Noack, Harald Kruggel-Emden
Characterizing material flow in sensor-based sorting systems using an instrumented particle. Autom. 68(4): 256-264 (2020) - [c62]Susanne Radtke, Benjamin Noack, Uwe D. Hanebeck:
Fully Decentralized Estimation Using Square-Root Decompositions. FUSION 2020: 1-8 - [c61]Christopher Funk, Benjamin Noack, Uwe D. Hanebeck:
Conservative Quantization of Fast Covariance Intersection. MFI 2020: 68-74
2010 – 2019
- 2019
- [j7]Eva Julia Schmitt
Gaussianity-Preserving Event-Based State Estimation With an FIR-Based Stochastic Trigger. IEEE Control. Syst. Lett. 3(3): 769-774 (2019) - [j6]Georg Maier, Florian Pfaff
Real-time multitarget tracking for sensor-based sorting - A new implementation of the auction algorithm for graphics processing units. J. Real Time Image Process. 16(6): 2261-2272 (2019) - [c60]Kailai Li, Daniel Frisch, Benjamin Noack, Uwe D. Hanebeck:
Geometry-driven Deterministic Sampling for Nonlinear Bingham Filtering. ECC 2019: 381-387 - [c59]Susanne Radtke, Benjamin Noack, Uwe D. Hanebeck:
Distributed Estimation with Partially Overlapping States based on Deterministic Sample-based Fusion. ECC 2019: 1822-1829 - [c58]Tobias Kronauer, Florian Pfaff, Benjamin Noack, Wei Tiant, Georg Maier, Uwe D. Hanebeck:
Feature-Aided Multitarget Tracking for Optical Belt Sorters. FUSION 2019: 1-8 - [c57]Benjamin Noack, Umut Orguner, Uwe D. Hanebeck:
Nonlinear Decentralized Data Fusion with Generalized Inverse Covariance Intersection. FUSION 2019: 1-7 - [c56]Susanne Radtke, Benjamin Noack, Uwe D. Hanebeck:
Distributed Estimation using Square Root Decompositions of Dependent Information. FUSION 2019: 1-8 - [c55]Susanne Radtke, Kailai Li, Benjamin Noack, Uwe D. Hanebeck:
Comparative Study of Track-to-Track Fusion Methods for Cooperative Tracking with Bearings-only Measurements. ICPS 2019: 236-241 - [c54]Selim Özgen, Saskia Kohn, Benjamin Noack, Uwe D. Hanebeck:
State Estimation with Model-Mismatch-Based Secrecy against Eavesdroppers. ICPS 2019: 808-812 - [i1]Kailai Li, Johannes Cox, Benjamin Noack, Uwe D. Hanebeck:
Improved Pose Graph Optimization for Planar Motions Using Riemannian Geometry on the Manifold of Dual Quaternions. CoRR abs/1907.13566 (2019) - 2018
- [j5]Jindrich Duník
Directional splitting of Gaussian density in non-linear random variable transformation. IET Signal Process. 12(9): 1073-1081 (2018) - [j4]Katharina Dormann, Benjamin Noack
Optimally Distributed Kalman Filtering with Data-Driven Communication. Sensors 18(4): 1034 (2018) - [c53]Florian Rosenthal
Scheduling of Measurement Transmission in Networked Control Systems Subject to Communication Constraints. ACC 2018: 5730-5736 - [c52]Mikhail Aristov, Benjamin Noack, Uwe D. Hanebeck, Jörn Müller-Quade:
Encrypted Multisensor Information Filtering. FUSION 2018: 1631-1637 - [c51]Susanne Radtke, Benjamin Noack, Uwe D. Hanebeck, Ondrej Straka:
Reconstruction of Cross-Correlations with Constant Number of Deterministic Samples. FUSION 2018: 1638-1645 - [c50]Selim Ozgen, Florian Rosenthal
Retrodiction of Data Association Probabilities via Convex Optimization. FUSION 2018: 2430-2436 - [c49]Kailai Li
Wavefront Orientation Estimation Based on Progressive Bingham Filtering. SDF 2018: 1-6 - 2017
- [j3]Florian Pfaff, Georg Maier, Mikhail Aristov, Benjamin Noack, Robin Gruna, Uwe D. Hanebeck, Thomas Längle, Jürgen Beyerer, Christoph Pieper, Harald Kruggel-Emden, Siegmar Wirtz, Viktor Scherer:
Real-time motion prediction using the chromatic offset of line scan cameras. Autom. 65(6): 369 (2017) - [j2]Benjamin Noack, Joris Sijs, Marc Reinhardt, Uwe D. Hanebeck
Decentralized data fusion with inverse covariance intersection. Autom. 79: 35-41 (2017) - [c48]Benjamin Noack, Joris Sijs, Uwe D. Hanebeck:
Inverse covariance intersection: New insights and properties. FUSION 2017: 1-8 - [c47]Florian Pfaff
Optimal distributed combined stochastic and set-membership state estimation. FUSION 2017: 1-10 - [c46]Florian Pfaff
Information form distributed Kalman filtering (IDKF) with explicit inputs. FUSION 2017: 1-8 - [c45]Katharina Dormann, Benjamin Noack, Uwe D. Hanebeck:
Distributed Kalman filtering with reduced transmission rate. MFI 2017: 253-259 - [c44]Florian Rosenthal
State estimation in networked control systems with delayed and lossy acknowledgments. MFI 2017: 435-441 - [c43]Florian Pfaff
Improving multitarget tracking using orientation estimates for sorting bulk materials. MFI 2017: 553-558 - 2016
- [c42]Jannik Steinbring, Benjamin Noack, Marc Reinhardt, Uwe D. Hanebeck:
Optimal sample-based fusion for distributed state estimation. FUSION 2016: 1600-1607 - [c41]Benjamin Noack, Florian Pfaff, Marcus Baum, Uwe D. Hanebeck:
State estimation considering negative information with switching Kalman and ellipsoidal filtering. FUSION 2016: 1945-1952 - [c40]Benjamin Noack, Joris Sijs, Uwe D. Hanebeck:
Algebraic analysis of data fusion with ellipsoidal intersection. MFI 2016: 365-370 - [c39]Georg Maier, Florian Pfaff
Fast multitarget tracking via strategy switching for sensor-based sorting. MFI 2016: 505-510 - [c38]Florian Pfaff
Simulation-based evaluation of predictive tracking for sorting bulk materials. MFI 2016: 511-516 - [c37]Florian Faion, Antonio Zea, Benjamin Noack, Jannik Steinbring, Uwe D. Hanebeck:
Camera- and IMU-based pose tracking for augmented reality. MFI 2016: 648-653 - 2015
- [j1]Marc Reinhardt, Benjamin Noack, Pablo O. Arambel, Uwe D. Hanebeck
Minimum Covariance Bounds for the Fusion under Unknown Correlations. IEEE Signal Process. Lett. 22(9): 1210-1214 (2015) - [c36]Benjamin Noack, Simon J. Julier, Uwe D. Hanebeck:
Treatment of biased and dependent sensor data in graph-based SLAM. FUSION 2015: 1862-1867 - [c35]Florian Pfaff
TrackSort: Predictive tracking for sorting uncooperative bulk materials. MFI 2015: 7-12 - [c34]Marcus Baum
Kalman filter-based SLAM with unknown data association using Symmetric Measurement Equations. MFI 2015: 49-53 - [c33]Benjamin Noack, Marcus Baum
State estimation for ellipsoidally constrained dynamic systems with set-membership pseudo measurements. MFI 2015: 297-302 - 2014
- [b1]Benjamin Noack:
State Estimation for Distributed Systems with Stochastic and Set-membership Uncertainties. Karlsruhe Institute of Technology, KIT Scientific Publishing 2014 - [c32]Marc Reinhardt, Benjamin Noack, Uwe D. Hanebeck:
Reconstruction of joint covariances in networked linear systems. CISS 2014: 1-6 - [c31]Jirí Ajgl, Miroslav Simandl, Marc Reinhardt, Benjamin Noack, Uwe D. Hanebeck:
Covariance Intersection in state estimation of dynamical systems. FUSION 2014: 1-7 - [c30]Benjamin Noack, Marc Reinhardt, Uwe D. Hanebeck:
On nonlinear track-to-track fusion with Gaussian mixtures. FUSION 2014: 1-8 - [c29]Marc Reinhardt, Benjamin Noack, Sanjeev Kulkarni, Uwe D. Hanebeck:
Distributed Kalman filtering in the presence of packet delays and losses. FUSION 2014: 1-7 - [c28]Joris Sijs, Leon Kester, Benjamin Noack:
A study on event triggering criteria for estimation. FUSION 2014: 1-8 - 2013
- [c27]Joris Sijs, Uwe D. Hanebeck, Benjamin Noack:
An empirical method to fuse partially overlapping state vectors for distributed state estimation. ECC 2013: 1615-1620 - [c26]Marc Reinhardt, Benjamin Noack, Uwe D. Hanebeck:
Advances in hypothesizing distributed Kalman filtering. FUSION 2013: 77-84 - [c25]Benjamin Noack, Simon J. Julier, Marc Reinhardt, Uwe D. Hanebeck:
Nonlinear federated filtering. FUSION 2013: 350-356 - [c24]Florian Pfaff, Benjamin Noack, Uwe D. Hanebeck:
Data validation in the presence of stochastic and set-membership uncertainties. FUSION 2013: 2125-2132 - [c23]Joris Sijs, Benjamin Noack, Uwe D. Hanebeck:
Event-based state estimation with negative information. FUSION 2013: 2192-2199 - 2012
- [c22]Benjamin Noack, Florian Pfaff
Optimal Kalman gains for combined stochastic and set-membership state estimation. CDC 2012: 4035-4040 - [c21]Marc Reinhardt, Benjamin Noack, Uwe D. Hanebeck:
Decentralized control based on globally optimal estimation. CDC 2012: 6247-6252 - [c20]Marc Reinhardt, Benjamin Noack, Uwe D. Hanebeck:
On optimal distributed Kalman filtering in non-ideal situations. FUSION 2012: 1020-1027 - [c19]Alessio Benavoli, Benjamin Noack:
Pushing Kalman's idea to the extremes. FUSION 2012: 1202-1209 - [c18]Benjamin Noack, Florian Pfaff, Uwe D. Hanebeck:
Combined stochastic and set-membership information filtering in multisensor systems. FUSION 2012: 1218-1224 - [c17]Marc Reinhardt, Benjamin Noack, Uwe D. Hanebeck:
Closed-form optimization of covariance intersection for low-dimensional matrices. FUSION 2012: 1891-1896 - [c16]Marc Reinhardt, Benjamin Noack, Uwe D. Hanebeck:
The Hypothesizing Distributed Kalman Filter. MFI 2012: 305-312 - 2011
- [c15]Benjamin Noack, Daniel Lyons, Matthias Nagel, Uwe D. Hanebeck:
Nonlinear information filtering for distributed multisensor data fusion. ACC 2011: 4846-4852 - [c14]Marcus Baum
Mixture Random Hypersurface Models for tracking multiple extended objects. CDC/ECC 2011: 3166-3171 - [c13]Johannes Schmid, Frederik Beutler, Benjamin Noack, Uwe D. Hanebeck
An Experimental Evaluation of Position Estimation Methods for Person Localization in Wireless Sensor Networks. EWSN 2011: 147-162 - [c12]Marcus Baum, Benjamin Noack, Frederik Beutler, Dominik Itte, Uwe D. Hanebeck:
Optimal Gaussian filtering for polynomial systems applied to association-free multi-target tracking. FUSION 2011: 1-8 - [c11]Benjamin Noack, Marcus Baum, Uwe D. Hanebeck:
Covariance intersection in nonlinear estimation based on pseudo Gaussian densities. FUSION 2011: 1-8 - [c10]Marc Reinhardt, Benjamin Noack, Marcus Baum, Uwe D. Hanebeck:
Analysis of set-theoretic and stochastic models for fusion under unknown correlations. FUSION 2011: 1-8 - 2010
- [c9]Achim Hekler, Daniel Lyons, Benjamin Noack, Uwe D. Hanebeck:
Nonlinear Model Predictive Control Considering Stochastic and Systematic Uncertainties with Sets of Densities. CCA 2010: 1337-1342 - [c8]Benjamin Noack:
Decentralized Reconstruction of Continuous Distributed Phenomena based on Discrete Measurements. AlgoSyn 2010: 65 - [c7]Marcus Baum, Benjamin Noack, Uwe D. Hanebeck:
Extended object and group tracking with Elliptic Random Hypersurface Models. FUSION 2010: 1-8 - [c6]Vesa Klumpp, Benjamin Noack, Marcus Baum, Uwe D. Hanebeck:
Combined set-theoretic and stochastic estimation: A comparison of the SSI and the CS filter. FUSION 2010: 1-8 - [c5]Benjamin Noack, Vesa Klumpp, Nikolay Petkov, Uwe D. Hanebeck:
Bounding linearization errors with sets of densities in approximate Kalman filtering. FUSION 2010: 1-8 - [c4]Evgeniya Bogatyrenko, Benjamin Noack, Uwe D. Hanebeck:
Reliable estimation of heart surface motion under stochastic and unknown but bounded systematic uncertainties. IROS 2010: 1862-1869 - [c3]Daniel Lyons, Benjamin Noack, Uwe D. Hanebeck:
A Log-Ratio Information Measure for Stochastic Sensor Management. SUTC/UMC 2010: 276-283
2000 – 2009
- 2009
- [c2]Benjamin Noack, Vesa Klumpp, Uwe D. Hanebeck:
State estimation with sets of densities considering stochastic and systematic errors. FUSION 2009: 1751-1758 - 2008
- [c1]Benjamin Noack, Vesa Klumpp, Dietrich Brunn, Uwe D. Hanebeck:
Nonlinear Bayesian estimation with convex sets of probability densities. FUSION 2008: 1-8
Coauthor Index
[j14] [j13] [c65] [j12] [j11] [j10] [c63] [j9] [j8] [c62] [c61] [j7] [j6] [c60] [c59] [c58] [c57] [c56] [c55] [c54] [i1] [j5] [j4] [c53] [c52] [c51] [c50] [c49] [j3] [j2] [c48] [c47] [c46] [c45] [c44] [c43] [c42] [c41] [c40] [c39] [c38] [c37] [j1] [c36] [c35] [c34] [c33] [c32] [c31] [c30] [c29] [c27] [c26] [c25] [c24] [c23] [c22] [c21] [c20] [c18] [c17] [c16] [c15] [c14] [c13] [c12] [c11] [c10] [c9] [c7] [c6] [c5] [c4] [c3] [c2] [c1]
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last updated on 2024-11-13 23:50 CET by the dblp team
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