Ute Schmid

67 papers and 559 indexed citations i.

About

Ute Schmid is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition and Computational Theory and Mathematics. According to data from OpenAlex, Ute Schmid has authored 67 papers receiving a total of 559 indexed citations (citations by other indexed papers that have themselves been cited), including 36 papers in Artificial Intelligence, 10 papers in Computer Vision and Pattern Recognition and 10 papers in Computational Theory and Mathematics. Recurrent topics in Ute Schmid’s work include Explainable Artificial Intelligence (XAI) (17 papers), Teaching and Learning Programming (7 papers) and Computability, Logic, AI Algorithms (6 papers). Ute Schmid is often cited by papers focused on Explainable Artificial Intelligence (XAI) (17 papers), Teaching and Learning Programming (7 papers) and Computability, Logic, AI Algorithms (6 papers). Ute Schmid collaborates with scholars based in Germany, United States and United Kingdom. Ute Schmid's co-authors include Emanuel Kitzelmann, Bettina Finzel, Stephen Muggleton, José Hernández‐Orallo, Tarek R. Besold, Michael Siebers, Katharina Weitz, Jens-Uwe Garbas, Alireza Tamaddoni‐Nezhad and Pierre Flener and has published in prestigious journals such as IEEE Transactions on Pattern Analysis and Machine Intelligence, Communications of the ACM and Information Sciences.

In The Last Decade

Co-authorship network of co-authors of Ute Schmid i

Fields of papers citing papers by Ute Schmid

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Countries citing papers authored by Ute Schmid

Since Specialization
Citations

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