Simon‐Martin Schröder

423 total citations
4 papers, 191 citations indexed

About

Simon‐Martin Schröder is a scholar working on Artificial Intelligence, Oceanography and Computer Vision and Pattern Recognition. According to data from OpenAlex, Simon‐Martin Schröder has authored 4 papers receiving a total of 191 indexed citations (citations by other indexed papers that have themselves been cited), including 3 papers in Artificial Intelligence, 1 paper in Oceanography and 1 paper in Computer Vision and Pattern Recognition. Recurrent topics in Simon‐Martin Schröder's work include Domain Adaptation and Few-Shot Learning (3 papers), Machine Learning and Data Classification (2 papers) and Advanced Image and Video Retrieval Techniques (1 paper). Simon‐Martin Schröder is often cited by papers focused on Domain Adaptation and Few-Shot Learning (3 papers), Machine Learning and Data Classification (2 papers) and Advanced Image and Video Retrieval Techniques (1 paper). Simon‐Martin Schröder collaborates with scholars based in Germany, France and United States. Simon‐Martin Schröder's co-authors include Reinhard Koch, Rainer Kiko, Svenja Christiansen, Bernd Christiansen, Henk‐Jan Hoving, Florian Schütte, Helena Hauss, Peter Brandt, Bruce H. Robison and Marc Picheral and has published in prestigious journals such as Limnology and Oceanography, IEEE Access and Sensors.

In The Last Decade

Simon‐Martin Schröder

4 papers receiving 186 citations

Peers

Simon‐Martin Schröder
Comparison fields: 5 of 78
  • Artificial Intelligence 62
  • Computer Vision and Pattern Recognition 58
  • Oceanography 35
  • Ecology 27
  • Media Technology 16
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Ping Lang China
Natalia Wawrzyniak Poland
Shenlu Jiang China
Boyang Yu China
Josep Quintana Spain
Benjamin Graham United States
Tomokazu MURAKAMI Japan
Asjad Amin Pakistan
Hieu Lê United States
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Citations per field, relative to Simon‐Martin Schröder
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Citations per year, relative to Simon‐Martin Schröder
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Countries citing papers authored by Simon‐Martin Schröder

Since Specialization
Citations

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

Fields of papers citing papers by Simon‐Martin Schröder

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Simon‐Martin Schröder. 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 Simon‐Martin Schröder. The network helps show where Simon‐Martin Schröder may publish in the future.

Co-authorship network of co-authors of Simon‐Martin Schröder

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

All Works

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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