Jörg Hendrik Kappes
- Computer Vision and Pattern Recognition top 5%
- Artificial Intelligence top 10%
- Biomedical Engineering
- Computer Networks and Communications
- Surgery
- Co-authors
- Christoph SchnörrStefan SchmidtMartin BergtholdtFred A. HamprechtBogdan SavchynskyyThorsten BeierBjoern AndresUllrich Köthe
- Topics
- Machine Learning and Algorithms (6 papers)Medical Image Segmentation Techniques (5 papers)Advanced Image and Video Retrieval Techniques (5 papers)
- Journals
- IEEE Transactions on Pattern Analysis and Machine IntelligenceInternational Journal of Computer VisionComputer Vision and Image Understanding
- Partner nations
- GermanyFranceUnited States
In The Last Decade
Jörg Hendrik Kappes
17 papers receiving 439 citations
Peers
Comparison fields: 5 of 59
- Computer Vision and Pattern Recognition 246
- Artificial Intelligence 140
- Biomedical Engineering 101
- Computer Networks and Communications 59
- Surgery 52
Countries citing papers authored by Jörg Hendrik Kappes
This map shows the geographic impact of Jörg Hendrik Kappes'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 Jörg Hendrik Kappes with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Jörg Hendrik Kappes more than expected).
Fields of papers citing papers by Jörg Hendrik Kappes
This network shows the impact of papers produced by Jörg Hendrik Kappes. 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 Jörg Hendrik Kappes. The network helps show where Jörg Hendrik Kappes may publish in the future.
Co-authorship network of co-authors of Jörg Hendrik Kappes
This figure shows the co-authorship network connecting the top 25 collaborators of Jörg Hendrik Kappes. A scholar is included among the top collaborators of Jörg Hendrik Kappes 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 Jörg Hendrik Kappes. Jörg Hendrik Kappes is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 1 | |
| 2 | 3 | |
| 3 | 7 | |
| 4 | 19 | |
| 5 | 22 | |
| 6 | 77 | |
| 7 | 19 | |
| 8 | 12 | |
| 9 | Global MAP-Optimality by Shrinking the Combinatorial Search Area with Convex Relaxation | 7 |
| 10 | 15 | |
| 11 | 5 | |
| 12 | 23 | |
| 13 | 26 | |
| 14 | 3 | |
| 15 | 44 | |
| 16 | 76 | |
| 17 | 90 |
About Jörg Hendrik Kappes
Jörg Hendrik Kappes is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence and Computer Networks and Communications, having authored 17 papers that have together received 449 indexed citations. Recurring topics across this work include Machine Learning and Algorithms (6 papers), Medical Image Segmentation Techniques (5 papers) and Advanced Image and Video Retrieval Techniques (5 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (246 citations), Structural Biology (9 citations) and Oral Surgery (43 citations). Jörg Hendrik Kappes has collaborated with scholars based in Germany, France and United States. Frequent co-authors include Christoph Schnörr, Stefan Schmidt, Martin Bergtholdt, Fred A. Hamprecht, Bogdan Savchynskyy, Thorsten Beier, Bjoern Andres, Ullrich Köthe, Vladimír Pekar and Sebastian P. M. Dries. Their work appears in journals such as IEEE Transactions on Pattern Analysis and Machine Intelligence, International Journal of Computer Vision and Computer Vision and Image Understanding.
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.