Peer Kröger

7.1k total citations · 2 hit papers
99 papers, 3.6k citations indexed

About

Peer Kröger is a scholar working on Artificial Intelligence, Signal Processing and Computer Vision and Pattern Recognition. According to data from OpenAlex, Peer Kröger has authored 99 papers receiving a total of 3.6k indexed citations (citations by other indexed papers that have themselves been cited), including 50 papers in Artificial Intelligence, 48 papers in Signal Processing and 27 papers in Computer Vision and Pattern Recognition. Recurrent topics in Peer Kröger's work include Data Management and Algorithms (47 papers), Advanced Clustering Algorithms Research (28 papers) and Data Mining Algorithms and Applications (12 papers). Peer Kröger is often cited by papers focused on Data Management and Algorithms (47 papers), Advanced Clustering Algorithms Research (28 papers) and Data Mining Algorithms and Applications (12 papers). Peer Kröger collaborates with scholars based in Germany, Canada and Denmark. Peer Kröger's co-authors include Hans‐Peter Kriegel, Arthur Zimek, Jörg Sander, Erich Schubert, Karin Kailing, Christian Böhm, Matthias Renz, H.-P. Kriegel, Elke Achtert and Alexey Pryakhin and has published in prestigious journals such as The Science of The Total Environment, Palaeogeography Palaeoclimatology Palaeoecology and Machine Learning.

In The Last Decade

Peer Kröger

89 papers receiving 3.4k citations

Hit Papers

align trajectories

What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

Clustering high-dimensional data

2009 732 citations Hans‐Peter Kriegel, Peer Kröger et al. profile →
Density‐based clustering

2011 554 citations Hans‐Peter Kriegel, Peer Kröger et al. Wiley Interdisciplinary Reviews Data Mining and Knowledge Discovery profile →

Peers

Countries citing papers authored by Peer Kröger

Since Specialization

Citations

This map shows the geographic impact of Peer Kröger's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Peer Kröger with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Peer Kröger more than expected).

Fields of papers citing papers by Peer Kröger

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Peer Kröger. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Peer Kröger. The network helps show where Peer Kröger may publish in the future.

Co-authorship network of co-authors of Peer Kröger

This figure shows the co-authorship network connecting the top 25 collaborators of Peer Kröger. A scholar is included among the top collaborators of Peer Kröger based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Peer Kröger. Peer Kröger is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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20 of 20 papers shown

#	Work	Indexed citations
1	Advancing data-driven process modeling in metal forming 2025 ·at - Automatisierungstechnik ·Mathias Liewald, Birgit Vogel‐Heuser, Thomas Bergs, Marco F. Huber, Peer Kröger	1
2	CoMadOut—a robust outlier detection algorithm based on CoMAD 2024 ·Machine Learning ·(unknown), Daniyal Kazempour, (unknown), Peer Kröger	2
3	Do good scores imply good embeddings? On the necessity of inspecting manifold learning evaluation results by multiple criteria 2024 ·Daniyal Kazempour, (unknown), (unknown), (unknown), Peer Kröger	0
4	Interactive Detection and Visualization of Ocean Carbon Regimes 2023 ·Helmholtz Centre for Ocean Research Kiel (GEOMAR) ·(unknown), Daniyal Kazempour, Lavinia Patara, Peer Kröger	0
5	Enhancing AIS Vessel Trajectories via Trip Detection 2023 ·(unknown), (unknown), (unknown), Peer Kröger	0
6	Detection and Tracking of Dynamic Ocean Carbon Uptake Regimes Built Upon Spatial Target-Driver Relationships via Adaptive Hierarchical Clustering 2023 ·Helmholtz Centre for Ocean Research Kiel (GEOMAR) ·(unknown), Daniyal Kazempour, Lavinia Patara, Peer Kröger	0
7	Enhancing cluster analysis via topological manifold learning 2023 ·Data Mining and Knowledge Discovery ·Moritz Herrmann, Daniyal Kazempour, Fabian Scheipl, Peer Kröger	5
8	Layer-Wise Relevance Propagation for Echo State Networks Applied to Earth System Variability 2022 ·Helmholtz Centre for Ocean Research Kiel (GEOMAR) ·(unknown), Peer Kröger, Martin Claus, (unknown)	3
9	Provenance analysis of cremated skeletal remains by stable isotopes 2020 ·Anthropologischer Anzeiger ·Gisela Grupe, (unknown), Peer Kröger, (unknown), (unknown), (unknown), (unknown), Frank Söllner	0
10	Evidence for sea spray effect on oxygen stable isotopes in bone phosphate — Approximation and correction using Gaussian Mixture Model clustering 2019 ·The Science of The Total Environment ·(unknown), (unknown), Peer Kröger, Christoph Mayr, (unknown), (unknown), Gisela Grupe	4
11	Using Gaussian Mixture Model clustering for multi‐isotope analysis of archaeological fish bones for palaeobiodiversity studies 2016 ·Rapid Communications in Mass Spectrometry ·(unknown), (unknown), Peer Kröger, Gisela Grupe	10
12	A Mutual Pruning Approach for RkNN Join Processing. 2013 ·BTW ·Tobias Emrich, Peer Kröger, (unknown), Matthias Renz, Andreas Züfle	1
13	Interpreting and Unifying Outlier Scores 2011 ·Hans‐Peter Kriegel, Peer Kröger, Erich Schubert, Arthur Zimek	166
14	Density‐based clustering breakdown → 2011 ·Wiley Interdisciplinary Reviews Data Mining and Knowledge Discovery ·Hans‐Peter Kriegel, Peer Kröger, Jörg Sander, Arthur Zimek	554
15	On Using Class-Labels in Evaluation of Clusterings 2010 ·RWTH Publications (RWTH Aachen) ·Ines Färber, Stephan Günnemann, Hans‐Peter Kriegel, Peer Kröger, Emmanuel Müller, Erich Schubert, Thomas Seidl, Arthur Zimek, Ludwig-Maximilians-Universität München	69
16	Generalizing the Optimality of Multi-Step k-Nearest Neighbor Query Processing 2007 ·Hans‐Peter Kriegel, Peer Kröger, Peter Kunath, Matthias Renz	12
17	Mining Hierarchies of Correlation Clusters 2006 ·Elke Achtert, Christian Böhm, Peer Kröger, Arthur Zimek	22
18	Efficient Query Processing in Arbitrary Subspaces Using Vector Approximations 2006 ·H.-P. Kriegel, Peer Kröger, Matthias Schubert, (unknown)	10
19	Density Connected Clustering with Local Subspace Preferences 2005 ·Christian Böhm, Karin Kailing, H.-P. Kriegel, Peer Kröger	108
20	Density-Connected Subspace Clustering for High-Dimensional Data 2004 ·Karin Kailing, Hans‐Peter Kriegel, Peer Kröger	225

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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