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ORCIDPeter Protzel
- > Home > Persons > Peter Protzel
Publications
- 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)- [i12]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) - 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) - [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) - 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) - [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 - [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 - [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 - [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) - [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) - 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 - [c47]Stefan Schubert, Peer Neubert, Johannes Pöschmann, Peter Protzel:
Circular Convolutional Neural Networks for Panoramic Images and Laser Data. IV 2019: 653-660 - 2018
- [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 - 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 - [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) - [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
- [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 - 2012
- [c20]Peer Neubert, Niko Sünderhauf, Peter Protzel:
From Saliency Based Image Features Towards Semantic Mapping. ROBOTIK 2012 - 2010
- [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 - 2008
- [c12]Peer Neubert, Peter Protzel, Teresa A. Vidal-Calleja, Simon Lacroix:
A fast visual line segment tracker. ETFA 2008: 353-360
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last updated on 2024-04-25 05:42 CEST by the dblp team
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