Federico M. Sukno
- Computer Vision and Pattern Recognition top 5%
- Signal Processing top 5%
- Radiology, Nuclear Medicine and Imaging top 10%
- Cardiology and Cardiovascular Medicine
- Biomedical Engineering
- Co-authors
- Alejandro F. FrangiJohn L. WaddingtonPaul F. WhelanCorné HoogendoornConstantine ButakoffSebastián OrdásCatalina Tobon‐GomezXavier Binefa
- Topics
- Face recognition and analysis (24 papers)Face and Expression Recognition (13 papers)3D Shape Modeling and Analysis (11 papers)
- Journals
- IEEE Transactions on Pattern Analysis and Machine IntelligenceIEEE Transactions on Image ProcessingMagnetic Resonance in Medicine
- Partner nations
- SpainIrelandUnited States
In The Last Decade
Federico M. Sukno
62 papers receiving 682 citations
Peers
Comparison fields: 5 of 100
- Computer Vision and Pattern Recognition 355
- Signal Processing 172
- Radiology, Nuclear Medicine and Imaging 143
- Cardiology and Cardiovascular Medicine 111
- Biomedical Engineering 111
Countries citing papers authored by Federico M. Sukno
This map shows the geographic impact of Federico M. Sukno'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 M. Sukno with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Federico M. Sukno more than expected).
Fields of papers citing papers by Federico M. Sukno
This network shows the impact of papers produced by Federico M. Sukno. 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 M. Sukno. The network helps show where Federico M. Sukno may publish in the future.
Co-authorship network of co-authors of Federico M. Sukno
This figure shows the co-authorship network connecting the top 25 collaborators of Federico M. Sukno. A scholar is included among the top collaborators of Federico M. Sukno 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 M. Sukno. Federico M. Sukno 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 | 1 | |
| 3 | 2 | |
| 4 | 2 | |
| 5 | 1 | |
| 6 | 14 | |
| 7 | 6 | |
| 8 | 4 | |
| 9 | 5 | |
| 10 | 25 | |
| 11 | 3 | |
| 12 | Rotationally Invariant 3D Shape Contexts using Asymmetry Patterns. | 6 |
| 13 | 66 | |
| 14 | 16 | |
| 15 | 4 | |
| 16 | 26 | |
| 17 | 13 | |
| 18 | 10 | |
| 19 | 6 | |
| 20 | AV@CAR: A Spanish Multichannel Multimodal Corpus for In-Vehicle Automatic Audio-Visual Speech Recognition | 19 |
About Federico M. Sukno
Federico M. Sukno is a scholar working on Computer Vision and Pattern Recognition, Computational Mathematics and Signal Processing, having authored 65 papers that have together received 707 indexed citations. Recurring topics across this work include Face recognition and analysis (24 papers), Face and Expression Recognition (13 papers) and 3D Shape Modeling and Analysis (11 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (355 citations), Signal Processing (172 citations) and Computational Mathematics (5 citations). Federico M. Sukno has collaborated with scholars based in Spain, Ireland and United States. Frequent co-authors include Alejandro F. Frangi, John L. Waddington, Paul F. Whelan, Corné Hoogendoorn, Constantine Butakoff, Sebastián Ordás, Catalina Tobon‐Gomez, Xavier Binefa, Joaquím Comas and Mathieu De Craene. Their work appears in journals such as IEEE Transactions on Pattern Analysis and Machine Intelligence, IEEE Transactions on Image Processing and Magnetic Resonance in Medicine.
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.