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ORCIDPeter Protzel
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- affiliation: Fakultät für Elektrotechnik und Informationstechnik, Technische Universität Chemnitz
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2020 – today
- 2024
[j13]Fangming Yuan
, Stefan Schubert, Peter Protzel, Peer Neubert:
Local Positional Graphs and Attentive Local Features for a Data and Runtime-Efficient Hierarchical Place Recognition Pipeline. IEEE Robotics Autom. Lett. 9(3): 2686-2693 (2024)- [c64]Kenny Schlegel, Dmitri A. Rachkovskij, Evgeny Osipov, Peter Protzel, Peer Neubert:
Learnable Weighted Superposition in HDC and its Application to Multi-channel Time Series Classification. IJCNN 2024: 1-7 - [c63]Markus Weißflog, Stefan Schubert, Peter Protzel, Peer Neubert:
Towards Revisiting Visual Place Recognition for Joining Submaps in Multimap SLAM$^\star $. TAROS (1) 2024: 94-106 - [i14]Fangming Yuan, Stefan Schubert, Peter Protzel, Peer Neubert:
Local positional graphs and attentive local features for a data and runtime-efficient hierarchical place recognition pipeline. CoRR abs/2403.10283 (2024) - [i13]Markus Weißflog, Peter Protzel, Peer Neubert:
FETCH: A Memory-Efficient Replay Approach for Continual Learning in Image Classification. CoRR abs/2407.12375 (2024) - [i12]Markus Weißflog, Stefan Schubert, Peter Protzel, Peer Neubert:
Towards Revisiting Visual Place Recognition for Joining Submaps in Multimap SLAM. CoRR abs/2407.12408 (2024) - 2023
- [c62]Markus Weißflog, Peter Protzel, Peer Neubert:
FETCH: A Memory-Efficient Replay Approach for Continual Learning in Image Classification. IDEAL 2023: 418-430 - 2022
- [j12]Kenny Schlegel, Peer Neubert, Peter Protzel:
A comparison of vector symbolic architectures. Artif. Intell. Rev. 55(6): 4523-4555 (2022) - [j11]Karim Haggag, Sven Lange, Tim Pfeifer, Peter Protzel:
A Credible and Robust Approach to Ego-Motion Estimation Using an Automotive Radar. IEEE Robotics Autom. Lett. 7(3): 6020-6027 (2022) - [c61]Kenny Schlegel, Peer Neubert, Peter Protzel:
HDC-MiniROCKET: Explicit Time Encoding in Time Series Classification with Hyperdimensional Computing. IJCNN 2022: 1-8 - [i11]Kenny Schlegel, Peer Neubert, Peter Protzel:
HDC-MiniROCKET: Explicit Time Encoding in Time Series Classification with Hyperdimensional Computing. CoRR abs/2202.08055 (2022) - [i10]Karim Haggag, Sven Lange, Tim Pfeifer, Peter Protzel:
A Credible and Robust approach to Ego-Motion Estimation using an Automotive Radar. CoRR abs/2204.04149 (2022) - 2021
- [j10]Stefan Schubert, Peer Neubert, Peter Protzel:
Graph-Based Non-Linear Least Squares Optimization for Visual Place Recognition in Changing Environments. IEEE Robotics Autom. Lett. 6(2): 811-818 (2021) - [j9]Peer Neubert, Stefan Schubert, Peter Protzel:
Resolving Place Recognition Inconsistencies Using Intra-Set Similarities. IEEE Robotics Autom. Lett. 6(2): 2084-2090 (2021) - [j8]Tim Pfeifer, Sven Lange, Peter Protzel:
Advancing Mixture Models for Least Squares Optimization. IEEE Robotics Autom. Lett. 6(2): 3941-3948 (2021) - [c60]Kenny Schlegel, Peter Weissig, Peter Protzel:
A blind-spot-aware optimization-based planner for safe robot navigation. ECMR 2021: 1-8 - [c59]Fangming Yuan, Peer Neubert, Stefan Schubert, Peter Protzel:
SoftMP: Attentive feature pooling for joint local feature detection and description for place recognition in changing environments. ICRA 2021: 5847-5853 - [c58]Stefan Schubert, Peer Neubert, Peter Protzel:
Beyond ANN: Exploiting Structural Knowledge for Efficient Place Recognition. ICRA 2021: 5861-5867 - [c57]Kenny Schlegel, Florian Mirus, Peer Neubert, Peter Protzel:
Multivariate Time Series Analysis for Driving Style Classification using Neural Networks and Hyperdimensional Computing. IV 2021: 602-609 - [c56]Johannes Pöschmann, Tim Pfeifer, Peter Protzel:
Optimization based 3D Multi-Object Tracking using Camera and Radar Data. IV 2021: 1116-1123 - [c55]Peer Neubert, Stefan Schubert, Kenny Schlegel, Peter Protzel:
Vector Semantic Representations as Descriptors for Visual Place Recognition. Robotics: Science and Systems 2021 - [c54]Stefan Schubert, Peer Neubert, Peter Protzel:
Fast and Memory Efficient Graph Optimization via ICM for Visual Place Recognition. Robotics: Science and Systems 2021 - [i9]Tim Pfeifer, Sven Lange, Peter Protzel:
Advancing Mixture Models for Least Squares Optimization. CoRR abs/2103.02472 (2021) - [i8]Stefan Schubert, Peer Neubert, Peter Protzel:
Beyond ANN: Exploiting Structural Knowledge for Efficient Place Recognition. CoRR abs/2103.08366 (2021) - 2020
- [c53]Stefan Schubert, Peer Neubert, Peter Protzel:
Unsupervised Learning Methods for Visual Place Recognition in Discretely and Continuously Changing Environments. ICRA 2020: 4372-4378 - [c52]Johannes Pöschmann, Tim Pfeifer, Peter Protzel:
Factor Graph based 3D Multi-Object Tracking in Point Clouds. IROS 2020: 10343-10350 - [c51]Kenny Schlegel, Peer Neubert, Peter Protzel:
Building a Navigation System for a Shopping Assistant Robot from Off-the-Shelf Components. TAROS 2020: 103-115 - [c50]Fangming Yuan, Peer Neubert, Peter Protzel:
LocalSPED: A Classification Pipeline that Can Learn Local Features for Place Recognition Using a Small Training Set. TAROS 2020: 209-213 - [i7]Stefan Schubert, Peer Neubert, Peter Protzel:
Unsupervised Learning Methods for Visual Place Recognition in Discretely and Continuously Changing Environments. CoRR abs/2001.08960 (2020) - [i6]Kenny Schlegel, Peer Neubert, Peter Protzel:
A comparison of Vector Symbolic Architectures. CoRR abs/2001.11797 (2020) - [i5]Johannes Pöschmann, Tim Pfeifer, Peter Protzel:
Factor Graph based 3D Multi-Object Tracking in Point Clouds. CoRR abs/2008.05309 (2020) - [i4]Stefan Schubert, Peer Neubert, Peter Protzel:
Graph-based non-linear least squares optimization for visual place recognition in changing environments. CoRR abs/2012.14766 (2020)
2010 – 2019
- 2019
- [j7]Peer Neubert, Stefan Schubert, Peter Protzel:
An Introduction to Hyperdimensional Computing for Robotics. Künstliche Intell. 33(4): 319-330 (2019) - [j6]Peer Neubert, Stefan Schubert, Peter Protzel:
A Neurologically Inspired Sequence Processing Model for Mobile Robot Place Recognition. IEEE Robotics Autom. Lett. 4(4): 3200-3207 (2019) - [c49]Stefan Schubert, Peer Neubert, Peter Protzel:
Towards combining a neocortex model with entorhinal grid cells for mobile robot localization. ECMR 2019: 1-8 - [c48]Tim Pfeifer, Peter Protzel:
Expectation-Maximization for Adaptive Mixture Models in Graph Optimization. ICRA 2019: 3151-3157 - [c47]Stefan Schubert, Peer Neubert, Johannes Pöschmann, Peter Protzel:
Circular Convolutional Neural Networks for Panoramic Images and Laser Data. IV 2019: 653-660 - [c46]Tim Pfeifer, Peter Protzel:
Incrementally learned Mixture Models for GNSS Localization. IV 2019: 1131-1138 - [i3]Tim Pfeifer, Peter Protzel:
Incrementally Learned Mixture Models for GNSS Localization. CoRR abs/1904.13279 (2019) - 2018
- [c45]Tim Pfeifer, Peter Protzel:
Robust Sensor Fusion with Self-Tuning Mixture Models. IROS 2018: 3678-3685 - [c44]Peer Neubert, Subutai Ahmad, Peter Protzel:
A Sequence-Based Neuronal Model for Mobile Robot Localization. KI 2018: 117-130 - [c43]Peer Neubert, Peter Protzel:
Towards Hypervector Representations for Learning and Planning with Schemas. KI 2018: 182-189 - [i2]Tim Pfeifer, Peter Protzel:
Expectation-Maximization for Adaptive Mixture Models in Graph Optimization. CoRR abs/1811.04748 (2018) - 2017
- [c42]Johannes Pöschmann, Peer Neubert, Stefan Schubert, Peter Protzel:
Synthesized semantic views for mobile robot localization. ECMR 2017: 1-6 - [c41]Peer Neubert, Stefan Schubert, Peter Protzel:
Sampling-based methods for visual navigation in 3D maps by synthesizing depth images. IROS 2017: 2492-2498 - [c40]Tim Pfeifer, Sven Lange, Peter Protzel:
Dynamic Covariance Estimation - A parameter free approach to robust Sensor Fusion. MFI 2017: 359-365 - [c39]Sven Lange, Peter Weissig, Andreas Uhlig, Peter Protzel:
TUC-Bot: A Microcontroller Based Robot for Education. RiE 2017: 201-213 - [c38]Stefan Schubert, Peer Neubert, Peter Protzel:
Towards Camera Based Navigation in 3D Maps by Synthesizing Depth Images. TAROS 2017: 601-616 - 2016
- [j5]Peer Neubert, Peter Protzel:
Beyond Holistic Descriptors, Keypoints, and Fixed Patches: Multiscale Superpixel Grids for Place Recognition in Changing Environments. IEEE Robotics Autom. Lett. 1(1): 484-491 (2016) - [c37]Tim Pfeifer, Peter Weissig, Sven Lange, Peter Protzel:
Robust factor graph optimization - a comparison for sensor fusion applications. ETFA 2016: 1-4 - [c36]Stefan Schubert, Peer Neubert, Peter Protzel:
How to Build and Customize a High-Resolution 3D Laserscanner Using Off-the-shelf Components. TAROS 2016: 314-326 - 2015
- [j4]Peer Neubert, Niko Sünderhauf, Peter Protzel:
Superpixel-based appearance change prediction for long-term navigation across seasons. Robotics Auton. Syst. 69: 15-27 (2015) - [c35]Peer Neubert, Peter Protzel:
Local region detector + CNN based landmarks for practical place recognition in changing environments. ECMR 2015: 1-6 - [c34]Peer Neubert, Peter Protzel:
Benchmarking superpixel descriptors. EUSIPCO 2015: 614-618 - 2014
- [c33]Martina Truschzinski, Helge U. Dinkelbach, Nicholas H. Müller, Peter Ohler, Fred Hamke, Peter Protzel:
Deducing human emotions by robots: Computing basic non-verbal expressions of performed actions during a work task. ISIC 2014: 1342-1347 - [c32]Peer Neubert, Peter Protzel:
Compact Watershed and Preemptive SLIC: On Improving Trade-offs of Superpixel Segmentation Algorithms. ICPR 2014: 996-1001 - [i1]Aitor Aladren, Sasa Bodiroza, Hamid Reza Chitsaz, J. J. Guerrero, Verena V. Hafner, Kris K. Hauser, Aleksandar Jevtic, Moslem Kazemi, Bruno Lara, Gonzalo López-Nicolás, Peer Neubert, Peter Protzel, Laurel D. Riek, Niko Sünderhauf, Chee Yap:
Proceedings of the 1st Workshop on Robotics Challenges and Vision (RCV2013). CoRR abs/1402.3213 (2014) - 2013
- [c31]Peer Neubert, Peter Protzel:
Evaluating Superpixels in Video: Metrics Beyond Figure-Ground Segmentation. BMVC 2013 - [c30]Peer Neubert, Niko Sünderhauf, Peter Protzel:
Appearance change prediction for long-term navigation across seasons. ECMR 2013: 198-203 - [c29]Sven Lange, Niko Sünderhauf, Peter Protzel:
Incremental smoothing vs. filtering for sensor fusion on an indoor UAV. ICRA 2013: 1773-1778 - [c28]Niko Sünderhauf, Peter Protzel:
Switchable constraints vs. max-mixture models vs. RRR - A comparison of three approaches to robust pose graph SLAM. ICRA 2013: 5198-5203 - [c27]Niko Sünderhauf, Marcus Obst, Sven Lange, Gerd Wanielik, Peter Protzel:
Switchable constraints and incremental smoothing for online mitigation of non-line-of-sight and multipath effects. Intelligent Vehicles Symposium 2013: 262-268 - 2012
- [c26]Sven Lange, Peter Protzel:
Cost-efficient mono-camera tracking system for a multirotor UAV aimed for hardware-in-the-loop experiments. SSD 2012: 1-6 - [c25]Niko Sünderhauf, Peter Protzel:
Towards robust graphical models for GNSS-based localization in urban environments. SSD 2012: 1-6 - [c24]Daniel Wunschel, Sven Lange, Peter Protzel:
Motion estimation for autonomous quadrocopter indoor flight. SSD 2012: 1-6 - [c23]Niko Sünderhauf, Peter Protzel:
Towards a robust back-end for pose graph SLAM. ICRA 2012: 1254-1261 - [c22]Niko Sünderhauf, Peter Protzel:
Switchable constraints for robust pose graph SLAM. IROS 2012: 1879-1884 - [c21]Niko Sünderhauf, Marcus Obst, Gerd Wanielik, Peter Protzel:
Multipath mitigation in GNSS-based localization using robust optimization. Intelligent Vehicles Symposium 2012: 784-789 - [c20]Peer Neubert, Niko Sünderhauf, Peter Protzel:
From Saliency Based Image Features Towards Semantic Mapping. ROBOTIK 2012 - 2011
- [c19]Niko Sünderhauf, Peter Protzel:
BRIEF-Gist - Closing the loop by simple means. IROS 2011: 1234-1241 - 2010
- [j3]Niko Sünderhauf, Peter Protzel:
Learning from Nature: Biologically Inspired Robot Navigation and SLAM - A Review. Künstliche Intell. 24(3): 215-221 (2010) - [c18]Niko Sünderhauf, Peter Protzel:
Beyond RatSLAM: Improvements to a biologically inspired SLAM system. ETFA 2010: 1-8 - [c17]Niko Sünderhauf, Peer Neubert, Peter Protzel:
The causal update filter - A novel biologically inspired filter paradigm for appearance-based SLAM. IROS 2010: 3969-3974 - [c16]Niko Sünderhauf, Peter Protzel:
From Neurons to Robots: Towards Efficient Biologically Inspired Filtering and SLAM. KI 2010: 341-348 - [c15]Sebastian Drews, Sven Lange, Peter Protzel:
Validating an Active Stereo System Using USARSim. SIMPAR 2010: 387-398
2000 – 2009
- 2009
- [c14]Sven Lange, Niko Sünderhauf, Peter Protzel:
A vision based onboard approach for landing and position control of an autonomous multirotor UAV in GPS-denied environments. ICAR 2009: 1-6 - [c13]Niko Sünderhauf, Peter Protzel:
Using image profiles and integral images for efficient calculation of sparse optical flow fields. ICAR 2009: 1-6 - 2008
- [c12]Peer Neubert, Peter Protzel, Teresa A. Vidal-Calleja, Simon Lacroix:
A fast visual line segment tracker. ETFA 2008: 353-360 - 2007
- [j2]Josef Renner, Peter Protzel:
Mobile Agenten für den Fernzugriff auf eingebettete Systeme (Mobile Agents for Remote Access to Embedded Systems). Autom. 55(8): 394-403 (2007) - 2006
- [c11]Niko Sünderhauf, Thomas Krause, Peter Protzel:
Bringing Robotics closer to Students - a Threefold Approach. ICRA 2006: 339-344 - 2005
- [c10]Niko Sünderhauf, Kurt Konolige, Simon Lacroix, Peter Protzel:
Visual Odometry Using Sparse Bundle Adjustment on an Autonomous Outdoor Vehicle. AMS 2005: 157-163 - [c9]Thomas Krause, Peter Protzel:
Einfaches Steuerungskonzept für mobile Roboter in dynamischen unstrukturierten Umgebungen. AMS 2005: 287-293 - [c8]Niko Sünderhauf, Thomas Krause, Peter Protzel:
RoboKing - Bringing Robotics closer to Pupils. ICRA 2005: 4254-4259 - 2003
- [c7]Thomas Krause, Pedro U. Lima, Peter Protzel:
Flugregler für ein autonomes Luftschiff. AMS 2003: 83-90 - 2002
- [j1]Achim Lewandowski, Peter Protzel:
Predicting time-varying functions with local models. Intell. Data Anal. 6(3): 257-265 (2002) - [c6]Lars Kindermann, Achim Lewandowski, Peter Protzel:
Finding the Optimal Continuous Model for Discrete Data by Neural Network Interpolation of Fractional Iteration. ICANN 2002: 1094-1099 - 2001
- [c5]Achim Lewandowski, Peter Protzel:
Approximation of Time-Varying Functions with Local Regression Models. ICANN 2001: 237-246 - [c4]Achim Lewandowski, Peter Protzel:
Predicting Time-Varying Functions with Local Models. IDA 2001: 44-52
1990 – 1999
- 1996
- [c3]Karim Mohraz, Peter Protzel:
FlexNet - A flexible neural network construction algorithm. ESANN 1996 - [c2]Joerg Wallrafen, Peter Protzel, Heribert Popp:
Genetically Optimized Neural Network Classifiers for Bankruptcy Prediction - An Empirical Study. HICSS (2) 1996: 419-426 - 1995
- [c1]Thomas Martinetz, Peter Protzel, Otto Gramckow, Günter Sörgel:
Neural Network Control for Steel Rolling Mills. SNN Symposium on Neural Networks 1995: 280-286
1980 – 1989
- 1987
- [b1]Peter Protzel:
Zuverlässigkeit von Nahbereichskommunikationsnetzen. Braunschweig University of Technology, Germany, VDI-Verlag 1987, ISBN 978-3-18-147110-4, pp. 1-182
Coauthor Index
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