Christoph Raab

440 total papers · 10.0k total citations
23 papers, 204 citations indexed

About

Christoph Raab is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition and Atomic and Molecular Physics, and Optics. According to data from OpenAlex, Christoph Raab has authored 23 papers receiving a total of 204 indexed citations (citations by other indexed papers that have themselves been cited), including 14 papers in Artificial Intelligence, 7 papers in Computer Vision and Pattern Recognition and 4 papers in Atomic and Molecular Physics, and Optics. Recurrent topics in Christoph Raab's work include Face and Expression Recognition (5 papers), Data Stream Mining Techniques (5 papers) and Domain Adaptation and Few-Shot Learning (3 papers). Christoph Raab is often cited by papers focused on Face and Expression Recognition (5 papers), Data Stream Mining Techniques (5 papers) and Domain Adaptation and Few-Shot Learning (3 papers). Christoph Raab collaborates with scholars based in Germany, Netherlands and United Kingdom. Christoph Raab's co-authors include Frank-Michael Schleif, J. Eschner, Pavel Bushev, R. Blatt, F. Schmidt‐Kaler, Christoph Becher, Christian Nölleke, Stephan Falke, Michael Biehl and Peter Tiňo and has published in prestigious journals such as Physical Review Letters, Neurocomputing and Pattern Recognition Letters.

In The Last Decade

Christoph Raab

20 papers receiving 195 citations

Author Peers

Peers are selected by citation overlap in the author's most active subfields. citations · hero ref

Author						Papers	Cites
Christoph Raab	138	53	33	32	17	23	204
Andrea Ceschini	146 1.1×	35 0.7×	14 0.4×	38 1.2×	6 0.4×	19	216
Navneet Sharma	109 0.8×	25 0.5×	39 1.2×	28 0.9×	8 0.5×	27	239
Shivani A. Kumar	173 1.3×	140 2.6×	7 0.2×	35 1.1×	7 0.4×	32	267
Sudip Sanyal	112 0.8×	44 0.8×	16 0.5×	6 0.2×	14 0.8×	26	235
Florian Neukart	163 1.2×	32 0.6×	22 0.7×	15 0.5×	5 0.3×	28	225
Tobias Stollenwerk	132 1.0×	52 1.0×	22 0.7×	27 0.8×	4 0.2×	23	230
Yang Lu	61 0.4×	9 0.2×	58 1.8×	61 1.9×	6 0.4×	33	224
Ibrahim Issa	131 0.9×	11 0.2×	39 1.2×	59 1.8×	7 0.4×	25	203
Xin Sun	160 1.2×	54 1.0×	25 0.8×	19 0.6×	6 0.4×	30	250
Pedro Adão	76 0.6×	14 0.3×	52 1.6×	21 0.7×	4 0.2×	18	158

Countries citing papers authored by Christoph Raab

Since Specialization

Citations

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

Fields of papers citing papers by Christoph Raab

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Christoph Raab

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

All Works

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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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