Andreas Spitz

1.3k citations
62 papers · 717 · h-index 12

Impact in

Papers in

    • Topic Modeling 14
    • Natural Language Processing Techniques 13
    • Advanced Text Analysis Techniques 7
    • Semantic Web and Ontologies 5
    • Advanced Graph Neural Networks 5
    • Handwritten Text Recognition Techniques 11
    • Image Retrieval and Classification Techniques 5

Andreas Spitz

59 papers receiving 667 citations

Peers

Andreas Spitz
Comparison fields: 5 of 90
  • Computer Vision and Pattern Recognition 319
  • Artificial Intelligence 240
  • Media Technology 65
  • Communication 39
  • Statistical and Nonlinear Physics 59
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Citations per field
00.5×10×14.7×
John Salerno · 1×
Citations per year

Countries citing papers authored by Andreas Spitz

Since Specialization
Citations

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

Fields of papers citing papers by Andreas Spitz

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside Andreas Spitz, 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 Andreas Spitz Line = papers co-authored together Andreas Spitz links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 62 papers — load more, or switch the sort, to bring in the rest.

#Work
1 1997182
2 2018104
3 202137
4 200230
5 199430
6 201424
7 201620
8 199916
9 202115
10 202015
11 201712
12 199511
13 199811
14
Style-Directed Document Recognition
199910
15 202110
16 201510
17 20169
18 20029
19 20089
20 20038

About Andreas Spitz

Andreas Spitz is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition, Statistical and Nonlinear Physics, Communication and Sociology and Political Science, having authored 62 papers that have together received 717 indexed citations. Recurring topics across this work include Topic Modeling (14 papers), Natural Language Processing Techniques (13 papers), Complex Network Analysis Techniques (12 papers), Handwritten Text Recognition Techniques (11 papers), Advanced Text Analysis Techniques (7 papers), Semantic Web and Ontologies (5 papers), Image Retrieval and Classification Techniques (5 papers) and Advanced Graph Neural Networks (5 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (319 citations), Artificial Intelligence (240 citations), Media Technology (65 citations), Communication (39 citations) and Statistical and Nonlinear Physics (59 citations). Andreas Spitz has collaborated with scholars based in Germany, United States and Switzerland. Frequent co-authors include Michael Gertz, Gerhard Reinelt, Guangming Dai, Xiaoyu Chen, Robert West, Ahmad Abu‐Akel, Penelope Sibun, Alan F. Smeaton, Emőke-Ágnes Horvát and Won-Yong Shin. Their work appears in journals such as PLoS ONE, International Journal on Document Analysis and Recognition (IJDAR), IEEE Transactions on Pattern Analysis and Machine Intelligence, Scientific Reports and Leonardo.

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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