Andreas Spitz
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- Handwritten Text Recognition Techniques 11
- Image Retrieval and Classification Techniques 5
- Artificial Intelligence top 5%
- Topic Modeling 14
- Natural Language Processing Techniques 13
- Advanced Text Analysis Techniques 7
- Advanced Graph Neural Networks 5
- Semantic Web and Ontologies 5
- Media Technology top 5%
- Communication top 10%
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- Complex Network Analysis Techniques 12
- Co-authors
- Michael GertzXiaoyu ChenGuangming DaiGerhard ReineltRobert WestAhmad Abu‐AkelAlan F. SmeatonPenelope Sibun
- Journals
- PLoS ONE (4 papers)International Journal on Document Analysis and Recognition (IJDAR) (2 papers)IEEE Transactions on Pattern Analysis and Machine Intelligence (2 papers)
- Partner nations
- GermanyUnited StatesSwitzerland
In The Last Decade
Andreas Spitz
59 papers receiving 667 citations
Peers
Comparison fields: 5 of 90
- Computer Vision and Pattern Recognition 319
- Artificial Intelligence 240
- Media Technology 65
- Communication 39
- Statistical and Nonlinear Physics 59
Countries citing papers authored by Andreas Spitz
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
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-authorship network
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.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | 2025 | 0 | |
| 2 | 2025 | 5 | |
| 3 | 2024 | 2 | |
| 4 | 2024 | 1 | |
| 5 | 2023 | 2 | |
| 6 | 2023 | 4 | |
| 7 | 2023 | 1 | |
| 8 | 2022 | 4 | |
| 9 | 2022 | 1 | |
| 10 | 2022 | 5 | |
| 11 | 2021 | 10 | |
| 12 | 2021 | 37 | |
| 13 | 2021 | 5 | |
| 14 | Exploring Significant Interactions in Live News. | 2018 | 1 |
| 15 | 2018 | 2 | |
| 16 | 2015 | 2 | |
| 17 | Style-Directed Document Recognition | 1999 | 10 |
| 18 | Automatic language identification | 1997 | 7 |
| 19 | International Association for Pattern Recognition Workshop on Document Analysis Systems | 1995 | 3 |
| 20 | Automatic recognition and representation of documents | 1988 | 5 |
About Andreas Spitz
Andreas Spitz is a scholar working on Health Informatics, Artificial Intelligence, Communication, Statistical and Nonlinear Physics and General Social Sciences, 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), Image Retrieval and Classification Techniques (5 papers), Advanced Graph Neural Networks (5 papers) and Semantic Web and Ontologies (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, Xiaoyu Chen, Guangming Dai, Gerhard Reinelt, Robert West, Ahmad Abu‐Akel, Alan F. Smeaton, Penelope Sibun, 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.