Federico Raue
- Computer Vision and Pattern Recognition top 2%
- Artificial Intelligence top 10%
- Signal Processing top 10%
- Media Technology top 10%
- Control and Systems Engineering
- Co-authors
- Andreas DengelJ.J. van HeesThomas M. BreuelMarcus LiwickiWonmin ByeonStanislav FrolovTobias HinzLuca Bertinetto
- Topics
- Advanced Vision and Imaging (4 papers)Advanced Image Processing Techniques (4 papers)Image and Signal Denoising Methods (3 papers)
- Journals
- IEEE Transactions on Pattern Analysis and Machine IntelligenceIEEE Transactions on Neural Networks and Learning SystemsNeural Networks
- Partner nations
- GermanySwitzerlandUnited States
In The Last Decade
Federico Raue
14 papers receiving 602 citations
Hit Papers
Peers
Comparison fields: 5 of 109
- Computer Vision and Pattern Recognition 399
- Artificial Intelligence 177
- Signal Processing 91
- Media Technology 52
- Control and Systems Engineering 25
Countries citing papers authored by Federico Raue
This map shows the geographic impact of Federico Raue'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 Federico Raue with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Federico Raue more than expected).
Fields of papers citing papers by Federico Raue
This network shows the impact of papers produced by Federico Raue. 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 Federico Raue. The network helps show where Federico Raue may publish in the future.
Co-authorship network of co-authors of Federico Raue
This figure shows the co-authorship network connecting the top 25 collaborators of Federico Raue. A scholar is included among the top collaborators of Federico Raue 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 Federico Raue. Federico Raue is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 0 | |
| 2 | 0 | |
| 3 | 6 | |
| 4 | 32 | |
| 5 | 0 | |
| 6 | 3 | |
| 7 | 0 | |
| 8 | 33 | |
| 9 | 2 | |
| 10 | 1 | |
| 11 | Audioclip: Extending Clip to Image, Text and Audiobreakdown → | 163 |
| 12 | 3 | |
| 13 | 11 | |
| 14 | 129 | |
| 15 | Hybrid Sequence to Sequence Model for Video Object Segmentation. | 1 |
| 16 | Reading Type Classification based on Generative Models and Bidirectional Long Short-Term Memory. | 3 |
| 17 | 243 | |
| 18 | 3 |
About Federico Raue
Federico Raue is a scholar working on Computer Vision and Pattern Recognition, Music and Media Technology, having authored 18 papers that have together received 633 indexed citations. Recurring topics across this work include Advanced Vision and Imaging (4 papers), Advanced Image Processing Techniques (4 papers) and Image and Signal Denoising Methods (3 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (399 citations), Signal Processing (91 citations) and Media Technology (52 citations). Federico Raue has collaborated with scholars based in Germany, Switzerland and United States. Frequent co-authors include Andreas Dengel, J.J. van Hees, Thomas M. Breuel, Marcus Liwicki, Wonmin Byeon, Stanislav Frolov, Tobias Hinz, Andreas Dengel, Luca Bertinetto and Syed Saqib Bukhari. Their work appears in journals such as IEEE Transactions on Pattern Analysis and Machine Intelligence, IEEE Transactions on Neural Networks and Learning Systems and Neural Networks.
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.