Oskar van Rest
- Computer Vision and Pattern Recognition top 5%
- Computer Networks and Communications top 10%
- Artificial Intelligence top 10%
- Signal Processing top 10%
- Information Systems
- Co-authors
- Hassan ChafiSungpack HongJinha KimHannes VoigtStefan PlantikowTobias LindaakerGeorge FletcherPablo Barceló
- Topics
- Graph Theory and Algorithms (5 papers)Advanced Database Systems and Queries (4 papers)Semantic Web and Ontologies (2 papers)
- Cited by
- Signal ProcessingComputer Vision and Pattern RecognitionComputer Networks and Communications
- Journals
- Proceedings of the VLDB EndowmentTU/e Research PortalProceedings of the 2022 International Conference on Management of Data
- Partner nations
- United StatesPolandChile
In The Last Decade
Oskar van Rest
5 papers receiving 216 citations
Peers
Comparison fields: 5 of 19
- Computer Vision and Pattern Recognition 166
- Computer Networks and Communications 140
- Artificial Intelligence 108
- Signal Processing 89
- Information Systems 34
Countries citing papers authored by Oskar van Rest
This map shows the geographic impact of Oskar van Rest'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 Oskar van Rest with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Oskar van Rest more than expected).
Fields of papers citing papers by Oskar van Rest
This network shows the impact of papers produced by Oskar van Rest. 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 Oskar van Rest. The network helps show where Oskar van Rest may publish in the future.
Co-authorship network of co-authors of Oskar van Rest
This figure shows the co-authorship network connecting the top 25 collaborators of Oskar van Rest. A scholar is included among the top collaborators of Oskar van Rest 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 Oskar van Rest. Oskar van Rest is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 40 | |
| 2 | 73 | |
| 3 | 13 | |
| 4 | 82 | |
| 5 | 21 |
About Oskar van Rest
Oskar van Rest is a scholar working on Computer Vision and Pattern Recognition, Signal Processing and Computer Networks and Communications, having authored 5 papers that have together received 229 indexed citations. Recurring topics across this work include Graph Theory and Algorithms (5 papers), Advanced Database Systems and Queries (4 papers) and Semantic Web and Ontologies (2 papers). The work is most often cited by research in Signal Processing (89 citations), Computer Vision and Pattern Recognition (166 citations) and Computer Networks and Communications (140 citations). Oskar van Rest has collaborated with scholars based in United States, Poland and Chile. Frequent co-authors include Hassan Chafi, Sungpack Hong, Jinha Kim, Hannes Voigt, Stefan Plantikow, Tobias Lindaaker, George Fletcher, Pablo Barceló, Zhe Wu and Marcelo Arenas. Their work appears in journals such as Proceedings of the VLDB Endowment, TU/e Research Portal and Proceedings of the 2022 International Conference on Management of Data.
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.