Thomas Seidl
Impact in
- Signal Processing top 0.2%
- Data Management and Algorithms
- Time Series Analysis and Forecasting
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- Advanced Image and Video Retrieval Techniques
- Image Retrieval and Classification Techniques
Papers in
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- Advanced Clustering Algorithms Research 54
- Data Stream Mining Techniques 25
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- Data Management and Algorithms 86
- Time Series Analysis and Forecasting 28
- Co-authors
- Hans‐Peter Kriegel (16 shared papers)Ira Assent (38 shared papers)Emmanuel Müller (29 shared papers)Stephan Günnemann (40 shared papers)Christian Beecks (48 shared papers)Philipp Kranen (16 shared papers)Ralph Krieger (16 shared papers)Marwan Hassani (29 shared papers)
- Journals
- Blood (7 papers)European Journal of Immunology (4 papers)Proceedings of the VLDB Endowment (4 papers)Knowledge and Information Systems (4 papers)Data Mining and Knowledge Discovery (3 papers)
- Partner nations
- GermanyUnited KingdomUnited States
In The Last Decade
Thomas Seidl
257 papers receiving 5.2k citations
Peers
Comparison fields: 5 of 171
- Signal Processing 1.7k
- Computer Vision and Pattern Recognition 1.6k
- Artificial Intelligence 2.2k
- Hematology 379
- Immunology 655
Countries citing papers authored by Thomas Seidl
This map shows the geographic impact of Thomas Seidl'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 Thomas Seidl with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Thomas Seidl more than expected).
Fields of papers citing papers by Thomas Seidl
This network shows the impact of papers produced by Thomas Seidl. 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 Thomas Seidl. The network helps show where Thomas Seidl may publish in the future.
Co-authors
The 25 scholars most cited alongside Thomas Seidl, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
Showing the 20 most-cited of 274 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 1998 | 294 | |
| 2 | 2010 | 166 | |
| 3 | 2000 | 163 | |
| 4 | 2009 | 158 | |
| 5 | MOA: Massive Online Analysis, a framework for stream classification and clustering. | 2010 | 135 |
| 6 | 1998 | 130 | |
| 7 | 2011 | 126 | |
| 8 | Efficient User-Adaptable Similarity Search in Large Multimedia Databases | 1997 | 116 |
| 9 | 2002 | 101 | |
| 10 | 2015 | 96 | |
| 11 | 1998 | 92 | |
| 12 | Nearest neighbor classification in 3D protein databases. | 1999 | 86 |
| 13 | 2002 | 85 | |
| 14 | 2012 | 84 | |
| 15 | 2011 | 84 | |
| 16 | 2003 | 81 | |
| 17 | 2007 | 80 | |
| 18 | 2012 | 77 | |
| 19 | 2010 | 73 | |
| 20 | 2015 | 71 |
About Thomas Seidl
Thomas Seidl is a scholar working on Artificial Intelligence, Signal Processing, Computer Vision and Pattern Recognition, Information Systems and Computer Networks and Communications, having authored 274 papers that have together received 5.6k indexed citations. Recurring topics across this work include Data Management and Algorithms (86 papers), Advanced Clustering Algorithms Research (54 papers), Advanced Image and Video Retrieval Techniques (51 papers), Data Mining Algorithms and Applications (49 papers), Image Retrieval and Classification Techniques (46 papers), Video Analysis and Summarization (36 papers), Time Series Analysis and Forecasting (28 papers) and Data Stream Mining Techniques (25 papers). The work is most often cited by research in Signal Processing (1.7k citations), Computer Vision and Pattern Recognition (1.6k citations), Artificial Intelligence (2.2k citations), Hematology (379 citations) and Immunology (655 citations). Thomas Seidl has collaborated with scholars based in Germany, United Kingdom and United States. Frequent co-authors include Hans‐Peter Kriegel, Ira Assent, Emmanuel Müller, Stephan Günnemann, Christian Beecks, Philipp Kranen, Ralph Krieger, Marwan Hassani, Ines Färber and Merih Seran Uysal. Their work appears in journals such as Blood, European Journal of Immunology, Proceedings of the VLDB Endowment, Knowledge and Information Systems and Data Mining and Knowledge Discovery.
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.