111 citations · 229 across the 12 of their papers we have counts for
12 papers
FETCH: A Memory-Efficient Replay Approach for Continual Learning in Image Classification
Markus Weißflog, Peter Protzel, Peer Neubert
Class-incremental continual learning is an important area of research, as static deep learning methods fail to adapt to changing tasks and data distributions. In previous works, pr…
Towards Revisiting Visual Place Recognition for Joining Submaps in Multimap SLAM
Markus Weißflog, Stefan Schubert, Peter Protzel +1
Visual SLAM is a key technology for many autonomous systems. However, tracking loss can lead to the creation of disjoint submaps in multimap SLAM systems like ORB-SLAM3. Because of…
Local positional graphs and attentive local features for a data and runtime-efficient hierarchical place recognition pipeline
Fangming Yuan, Stefan Schubert, Peter Protzel +1
Large-scale applications of Visual Place Recognition (VPR) require computationally efficient approaches. Further, a well-balanced combination of data-based and training-free approa…
Visual Place Recognition: A Tutorial
Stefan Schubert, Peer Neubert, Sourav Garg +2
Localization is an essential capability for mobile robots. A rapidly growing field of research in this area is Visual Place Recognition (VPR), which is the ability to recognize pre…
HDC-MiniROCKET: Explicit Time Encoding in Time Series Classification with Hyperdimensional Computing
Kenny Schlegel, Peer Neubert, Peter Protzel
Classification of time series data is an important task for many application domains. One of the best existing methods for this task, in terms of accuracy and computation time, is…
What makes visual place recognition easy or hard?
Stefan Schubert, Peer Neubert
Visual place recognition is a fundamental capability for the localization of mobile robots. It places image retrieval in the practical context of physical agents operating in a phy…
Beyond ANN: Exploiting Structural Knowledge for Efficient Place Recognition
Stefan Schubert, Peer Neubert, Peter Protzel
Visual place recognition is the task of recognizing same places of query images in a set of database images, despite potential condition changes due to time of day, weather or seas…
Hyperdimensional computing as a framework for systematic aggregation of image descriptors
Peer Neubert, Stefan Schubert
Image and video descriptors are an omnipresent tool in computer vision and its application fields like mobile robotics. Many hand-crafted and in particular learned image descriptor…
Graph-based non-linear least squares optimization for visual place recognition in changing environments
Stefan Schubert, Peer Neubert, Peter Protzel
Visual place recognition is an important subproblem of mobile robot localization. Since it is a special case of image retrieval, the basic source of information is the pairwise sim…
Unsupervised Learning Methods for Visual Place Recognition in Discretely and Continuously Changing Environments
Stefan Schubert, Peer Neubert, Peter Protzel
Visual place recognition in changing environments is the problem of finding matchings between two sets of observations, a query set and a reference set, despite severe appearance c…
A comparison of Vector Symbolic Architectures
Kenny Schlegel, Peer Neubert, Peter Protzel
Vector Symbolic Architectures combine a high-dimensional vector space with a set of carefully designed operators in order to perform symbolic computations with large numerical vect…
Proceedings of the 1st Workshop on Robotics Challenges and Vision (RCV2013)
Aitor Aladren, Sasa Bodiroza, Hamidreza Chitsaz +12
Proceedings of the 1st Workshop on Robotics Challenges and Vision (RCV2013)