G Seegmliller

About

G Seegmliller is a scholar working on Computational Theory and Mathematics, Artificial Intelligence and Computer Vision and Pattern Recognition. According to data from OpenAlex, G Seegmliller has authored 10 papers receiving a total of 154 indexed citations (citations by other indexed papers that have themselves been cited), including 3 papers in Computational Theory and Mathematics, 1 paper in Artificial Intelligence and 1 paper in Computer Vision and Pattern Recognition. Recurrent topics in G Seegmliller’s work include Matrix Theory and Algorithms (1 paper), Formal Methods in Verification (1 paper) and Augmented Reality Applications (1 paper). G Seegmliller is often cited by papers focused on Matrix Theory and Algorithms (1 paper), Formal Methods in Verification (1 paper) and Augmented Reality Applications (1 paper). G Seegmliller collaborates with scholars based in Italy, India and Austria. G Seegmliller's co-authors include P Brinch, D Barstow, D Luckham, Niklaus Wirth, Hansen Gries, J Stoer, W Brauer, C Moler, Hansen Gries and Mariangiola Dezani-Ciancaglini and has published in prestigious journals such as Lecture notes in computer science.

In The Last Decade

Co-authorship network of co-authors of G Seegmliller i

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Fields of papers citing papers by G Seegmliller

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Countries citing papers authored by G Seegmliller

Since Specialization

Citations

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

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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