Raoul Rivas
- Computer Vision and Pattern Recognition top 5%
- Computer Networks and Communications top 10%
- Sociology and Political Science
- Human-Computer Interaction top 5%
- Signal Processing top 10%
- Co-authors
- Klara NahrstedtAhsan ArefinWanmin WuZhenyu YangZixia HuangShu ShiPooja AgarwalMorihiko Tamai
- Topics
- Multimedia Communication and Technology (12 papers)Image and Video Quality Assessment (11 papers)Peer-to-Peer Network Technologies (7 papers)
- Cited by
- Human-Computer InteractionComputer Vision and Pattern RecognitionComputer Networks and Communications
- Partner nations
- United StatesJapanUnited Kingdom
In The Last Decade
Raoul Rivas
18 papers receiving 282 citations
Peers
Comparison fields: 5 of 43
- Computer Vision and Pattern Recognition 203
- Computer Networks and Communications 113
- Sociology and Political Science 112
- Human-Computer Interaction 68
- Signal Processing 44
Countries citing papers authored by Raoul Rivas
This map shows the geographic impact of Raoul Rivas'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 Raoul Rivas with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Raoul Rivas more than expected).
Fields of papers citing papers by Raoul Rivas
This network shows the impact of papers produced by Raoul Rivas. 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 Raoul Rivas. The network helps show where Raoul Rivas may publish in the future.
Co-authorship network of co-authors of Raoul Rivas
This figure shows the co-authorship network connecting the top 25 collaborators of Raoul Rivas. A scholar is included among the top collaborators of Raoul Rivas 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 Raoul Rivas. Raoul Rivas 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 | 2 | |
| 3 | 9 | |
| 4 | 8 | |
| 5 | 2 | |
| 6 | 7 | |
| 7 | 8 | |
| 8 | 2 | |
| 9 | 11 | |
| 10 | 5 | |
| 11 | 4 | |
| 12 | 8 | |
| 13 | 37 | |
| 14 | 15 | |
| 15 | 9 | |
| 16 | 8 | |
| 17 | 8 | |
| 18 | 124 | |
| 19 | 43 | |
| 20 | 0 |
About Raoul Rivas
Raoul Rivas is a scholar working on Computer Vision and Pattern Recognition, Computer Networks and Communications and Hardware and Architecture, having authored 20 papers that have together received 311 indexed citations. Recurring topics across this work include Multimedia Communication and Technology (12 papers), Image and Video Quality Assessment (11 papers) and Peer-to-Peer Network Technologies (7 papers). The work is most often cited by research in Human-Computer Interaction (68 citations), Computer Vision and Pattern Recognition (203 citations) and Computer Networks and Communications (113 citations). Raoul Rivas has collaborated with scholars based in United States, Japan and United Kingdom. Frequent co-authors include Klara Nahrstedt, Ahsan Arefin, Wanmin Wu, Zhenyu Yang, Zixia Huang, Shu Shi, Pooja Agarwal, Morihiko Tamai, Hoàng Việt Nguyễn and Gregorij Kurillo. Their work appears in journals such as Multimedia Tools and Applications, Mobile Networks and Applications and IEEE Multimedia.
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.