Karsten Luebke

453 citations
9 papers · 15 indexed · h-index 3
Topics
Neural Networks and Applications (3 papers)Face and Expression Recognition (2 papers)Advanced Statistical Methods and Models (2 papers)
Partner nations
GermanyUnited States

In The Last Decade

Karsten Luebke

6 papers receiving 15 citations

Peers

Karsten Luebke
Comparison fields: 5 of 18
  • Artificial Intelligence 10
  • Computer Vision and Pattern Recognition 5
  • Signal Processing 2
  • Computational Theory and Mathematics 2
  • Analytical Chemistry 2
Replace Michaël Quisquater with:
Michaël Quisquater Belgium
Minoru Saeki Japan
Pierre Karpman France
Abdelwahab Heba Saudi Arabia
Leslie Rice United States
Stefan Heyse Germany
Naomi Benger Australia
Igor Gitman United States
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C. Fassnacht Germany
Karsten Luebke relative to Michaël Quisquater Belgium Michaël Quisquater's profile →
Citations per field
00.5×1.5×
Michaël Quisquater · 1×
Citations per year

Countries citing papers authored by Karsten Luebke

Since Specialization
Citations

This map shows the geographic impact of Karsten Luebke'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 Karsten Luebke with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Karsten Luebke more than expected).

Fields of papers citing papers by Karsten Luebke

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Karsten Luebke. 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 Karsten Luebke. The network helps show where Karsten Luebke may publish in the future.

Co-authorship network of co-authors of Karsten Luebke

This figure shows the co-authorship network connecting the top 25 collaborators of Karsten Luebke. A scholar is included among the top collaborators of Karsten Luebke 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 Karsten Luebke. Karsten Luebke is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

9 of 9 papers shown
#WorkIndexed citations
1 0
2 1
3 2
4
Response Surface Methodology for Optimizing Hyper Parameters
4
5
Prediction Optimal Classification of Business Phases
0
6 4
7 3
8
A Note on the Dimension of the Projection Space in a Latent Factor Regression Model with Application to Business Cycle Classification
0
9 1

About Karsten Luebke

Karsten Luebke is a scholar working on Statistics and Probability, Artificial Intelligence and Media Technology, having authored 9 papers that have together received 15 indexed citations. Recurring topics across this work include Neural Networks and Applications (3 papers), Face and Expression Recognition (2 papers) and Advanced Statistical Methods and Models (2 papers). The work is most often cited by research in Artificial Intelligence (10 citations), Software (1 citation) and Computer Vision and Pattern Recognition (5 citations). Karsten Luebke has collaborated with scholars based in Germany and United States. Frequent co-authors include Claus Weihs, Andreas Christmann and Sebastian Sauer. Their work appears in journals such as Pattern Recognition, Computational Statistics & Data Analysis and Advances in Data Analysis and Classification.

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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