Michael Eckmann

447 citations
13 papers · 357 · h-index 8

Impact in

Papers in

Michael Eckmann

13 papers receiving 336 citations

Peers

Michael Eckmann
Comparison fields: 5 of 72
  • Computer Vision and Pattern Recognition 258
  • Statistics, Probability and Uncertainty 36
  • Media Technology 34
  • Computer Science Applications 14
  • Artificial Intelligence 75
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Chao Du China
Davide Eynard Switzerland
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Citations per year

Countries citing papers authored by Michael Eckmann

Since Specialization
Citations

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

Fields of papers citing papers by Michael Eckmann

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 10 scholars most cited alongside Michael Eckmann, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Michael Eckmann Line = papers co-authored together Michael Eckmann links everyone, so they are left out of the graph.

All Works

13 of 13 papers shown
#Work
1 2001135
2 200456
3 201347
4 201135
5 201227
6 201423
7 201316
8 201511
9
Discrete mathematics/structures: how do we deal with the late appreciation problem?
20093
10
A content-based image retrieval programming assignments for introductory computer science courses
20111
11 20081
12 20011
13
Sifting for better features to track: exploiting time and space
20071

About Michael Eckmann

Michael Eckmann is a scholar working on Computer Vision and Pattern Recognition, Computer Science Applications, Aerospace Engineering, Artificial Intelligence and Information Systems, having authored 13 papers that have together received 357 indexed citations. Recurring topics across this work include Advanced Image and Video Retrieval Techniques (3 papers), Advanced Vision and Imaging (3 papers), Video Surveillance and Tracking Methods (3 papers), Infrared Target Detection Methodologies (2 papers), Robotics and Sensor-Based Localization (2 papers), Digital Media Forensic Detection (2 papers), Information Systems Theories and Implementation (1 paper) and Information Retrieval and Search Behavior (1 paper). The work is most often cited by research in Computer Vision and Pattern Recognition (258 citations), Statistics, Probability and Uncertainty (36 citations), Media Technology (34 citations), Computer Science Applications (14 citations) and Artificial Intelligence (75 citations). Michael Eckmann has collaborated with scholars based in United States, Brazil and Germany. Frequent co-authors include T.E. Boult, Ross J. Micheals, Xiang Gao, Anderson De Rezende Rocha, Walter J. Scheirer, Jacques Wainer, Terrance E. Boult, Michael J. Wilber, Siome Klein Goldenstein and David Gries. Their work appears in journals such as Communications of the ACM, Scientometrics, Image and Vision Computing, Proceedings of the IEEE and Pattern Recognition Letters.

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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