Sandro Vega-Pons
Impact in
- Artificial Intelligence top 5%
- Advanced Clustering Algorithms Research
- Text and Document Classification Technologies
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- Face and Expression Recognition
Papers in
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- Face and Expression Recognition 4
- Medical Image Segmentation Techniques 2
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- Advanced Clustering Algorithms Research 5
- Co-authors
- José Ruíz-Shulcloper (4 shared papers)Paolo Avesani (4 shared papers)Seyed Mostafa Kia (1 shared paper)Michael Andric (1 shared paper)Andrea Passerini (1 shared paper)Nathan Weisz (1 shared paper)Uri Hasson (1 shared paper)Angelo Bifone (1 shared paper)
In The Last Decade
Sandro Vega-Pons
10 papers receiving 505 citations
Sandro Vega-Pons's Hit Papers
Peers
Comparison fields: 5 of 86
- Artificial Intelligence 353
- Computer Vision and Pattern Recognition 191
- Statistical and Nonlinear Physics 107
- Signal Processing 87
- Media Technology 51
Countries citing papers authored by Sandro Vega-Pons
This map shows the geographic impact of Sandro Vega-Pons'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 Sandro Vega-Pons with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Sandro Vega-Pons more than expected).
Fields of papers citing papers by Sandro Vega-Pons
This network shows the impact of papers produced by Sandro Vega-Pons. 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 Sandro Vega-Pons. The network helps show where Sandro Vega-Pons may publish in the future.
Co-authors
The 12 scholars most cited alongside Sandro Vega-Pons, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | A SURVEY OF CLUSTERING ENSEMBLE ALGORITHMS Hit paper breakdown → | 2011 | 386 |
| 2 | 2010 | 69 | |
| 3 | 2011 | 16 | |
| 4 | 2017 | 13 | |
| 5 | 2014 | 12 | |
| 6 | 2017 | 11 | |
| 7 | 2008 | 8 | |
| 8 | 2014 | 7 | |
| 9 | 2013 | 7 | |
| 10 | 2011 | 4 |
About Sandro Vega-Pons
Sandro Vega-Pons is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence, Cognitive Neuroscience, Signal Processing and Statistical and Nonlinear Physics, having authored 10 papers that have together received 533 indexed citations. Recurring topics across this work include Advanced Clustering Algorithms Research (5 papers), Face and Expression Recognition (4 papers), Functional Brain Connectivity Studies (3 papers), Medical Image Segmentation Techniques (2 papers), Neural dynamics and brain function (2 papers), Data Management and Algorithms (2 papers), Complex Network Analysis Techniques (2 papers) and Fetal and Pediatric Neurological Disorders (1 paper). The work is most often cited by research in Artificial Intelligence (353 citations), Computer Vision and Pattern Recognition (191 citations), Statistical and Nonlinear Physics (107 citations), Signal Processing (87 citations) and Media Technology (51 citations). Sandro Vega-Pons has collaborated with scholars based in Italy, Austria and Germany. Frequent co-authors include José Ruíz-Shulcloper, Paolo Avesani, Seyed Mostafa Kia, Michael Andric, Andrea Passerini, Nathan Weisz, Uri Hasson, Angelo Bifone, Emanuele Olivetti and Luca Dodero. Their work appears in journals such as Frontiers in Neuroscience, Pattern Recognition Letters, Neurocomputing, Pattern Recognition and International Journal of Pattern Recognition and Artificial Intelligence.
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.