Nils T. Siebel
- Computer Vision and Pattern Recognition top 10%
- Artificial Intelligence
- Electrical and Electronic Engineering
- Control and Systems Engineering
- Industrial and Manufacturing Engineering
- Co-authors
- Gerald SommerStephen J. MaybankYohannes KassahunDaniel RodríguezManoranjan SatpathyStephen CookS. Grunewald
- Topics
- Evolutionary Algorithms and Applications (5 papers)Neural Networks and Applications (3 papers)Metaheuristic Optimization Algorithms Research (3 papers)
- Journals
- Journal of Software Maintenance and Evolution Research and PracticeInternational Journal of Hybrid Intelligent Systems
- Partner nations
- GermanyUnited Kingdom
In The Last Decade
Nils T. Siebel
11 papers receiving 157 citations
Peers
Comparison fields: 5 of 38
- Computer Vision and Pattern Recognition 89
- Artificial Intelligence 80
- Electrical and Electronic Engineering 26
- Control and Systems Engineering 19
- Industrial and Manufacturing Engineering 18
Countries citing papers authored by Nils T. Siebel
This map shows the geographic impact of Nils T. Siebel'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 Nils T. Siebel with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Nils T. Siebel more than expected).
Fields of papers citing papers by Nils T. Siebel
This network shows the impact of papers produced by Nils T. Siebel. 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 Nils T. Siebel. The network helps show where Nils T. Siebel may publish in the future.
Co-authorship network of co-authors of Nils T. Siebel
This figure shows the co-authorship network connecting the top 25 collaborators of Nils T. Siebel. A scholar is included among the top collaborators of Nils T. Siebel 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 Nils T. Siebel. Nils T. Siebel is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 9 | |
| 2 | 8 | |
| 3 | 3 | |
| 4 | 14 | |
| 5 | 47 | |
| 6 | 11 | |
| 7 | 5 | |
| 8 | 3 | |
| 9 | The ADVISOR Visual Surveillance System | 57 |
| 10 | 3 | |
| 11 | 8 |
About Nils T. Siebel
Nils T. Siebel is a scholar working on Software, Media Technology and Artificial Intelligence, having authored 11 papers that have together received 168 indexed citations. Recurring topics across this work include Evolutionary Algorithms and Applications (5 papers), Neural Networks and Applications (3 papers) and Metaheuristic Optimization Algorithms Research (3 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (89 citations), Artificial Intelligence (80 citations) and Software (8 citations). Nils T. Siebel has collaborated with scholars based in Germany and United Kingdom. Frequent co-authors include Gerald Sommer, Stephen J. Maybank, Yohannes Kassahun, Daniel Rodríguez, Manoranjan Satpathy, Stephen Cook and S. Grunewald. Their work appears in journals such as Journal of Software Maintenance and Evolution Research and Practice and International Journal of Hybrid Intelligent Systems.
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.