Reiner Lenz

1.8k total citations
104 papers, 1.0k citations indexed

About

Reiner Lenz is a scholar working on Computer Vision and Pattern Recognition, Atomic and Molecular Physics, and Optics and Media Technology. According to data from OpenAlex, Reiner Lenz has authored 104 papers receiving a total of 1.0k indexed citations (citations by other indexed papers that have themselves been cited), including 64 papers in Computer Vision and Pattern Recognition, 44 papers in Atomic and Molecular Physics, and Optics and 19 papers in Media Technology. Recurrent topics in Reiner Lenz's work include Color Science and Applications (41 papers), Image Retrieval and Classification Techniques (26 papers) and Visual perception and processing mechanisms (15 papers). Reiner Lenz is often cited by papers focused on Color Science and Applications (41 papers), Image Retrieval and Classification Techniques (26 papers) and Visual perception and processing mechanisms (15 papers). Reiner Lenz collaborates with scholars based in Sweden, Japan and South Africa. Reiner Lenz's co-authors include Peter Meer, P.-E. Danielsson, Anders Liljeborg, N. Åslund, Kjell Carlsson, Lars Majlof, Timo Jääskeläinen, Jussi Parkkinen, Markku Hauta‐Kasari and Per‐Erik Danielsson and has published in prestigious journals such as SHILAP Revista de lepidopterología, Scientific Reports and IEEE Transactions on Image Processing.

In The Last Decade

Reiner Lenz

93 papers receiving 930 citations

Peers

Reiner Lenz
Comparison fields: 5 of 122
  • Computer Vision and Pattern Recognition 537
  • Atomic and Molecular Physics, and Optics 295
  • Media Technology 186
  • Biomedical Engineering 122
  • Cognitive Neuroscience 114
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Citations per field, relative to Reiner Lenz
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Citations per year, relative to Reiner Lenz
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Countries citing papers authored by Reiner Lenz

Since Specialization
Citations

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

Fields of papers citing papers by Reiner Lenz

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Reiner Lenz

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

All Works

20 of 20 papers shown
# Work Indexed citations
1 10
2 5
3
RGB Filter design using the properties of the weibull manifold
1
4 29
5 10
6
Color Semantics for Image Indexing
19
7 1
8 3
9 10
10 10
11 14
12 6
13 0
14 4
15 0
16 1
17 1
18
Unsupervised Parallel Feature Extraction from First Principles
2
19 43
20 2

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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