Federico Lecumberry

67 total papers · 528 total citations
30 papers, 341 citations indexed

About

Federico Lecumberry is a scholar working on Computer Vision and Pattern Recognition, Signal Processing and Molecular Biology. According to data from OpenAlex, Federico Lecumberry has authored 30 papers receiving a total of 341 indexed citations (citations by other indexed papers that have themselves been cited), including 11 papers in Computer Vision and Pattern Recognition, 8 papers in Signal Processing and 4 papers in Molecular Biology. Recurrent topics in Federico Lecumberry's work include Face and Expression Recognition (6 papers), Biometric Identification and Security (5 papers) and Face recognition and analysis (4 papers). Federico Lecumberry is often cited by papers focused on Face and Expression Recognition (6 papers), Biometric Identification and Security (5 papers) and Face recognition and analysis (4 papers). Federico Lecumberry collaborates with scholars based in Uruguay, United States and France. Federico Lecumberry's co-authors include Guillermo Sapiro, Alicia Fernández, Sriram Subramaniam, Alberto Bartesaghi, Ignacio Ramírez, J.T. Nunes, Guillermo Sapiro, Eileen Armstrong, J. Matías Di Martino and G. Seroussi and has published in prestigious journals such as Scientific Reports, IEEE Transactions on Image Processing and BMC Bioinformatics.

In The Last Decade

Federico Lecumberry

27 papers receiving 324 citations

Author Peers

Peers are selected by citation overlap in the author's most active subfields. citations · hero ref

Author Last Decade Papers Cites
Federico Lecumberry 83 68 61 40 40 30 341
N. Kasthuri 27 0.3× 27 0.4× 64 1.0× 28 0.7× 41 1.0× 45 320
Toufiq Parag 190 2.3× 39 0.6× 47 0.8× 10 0.3× 20 0.5× 21 344
Norman Wittels 79 1.0× 12 0.2× 42 0.7× 34 0.8× 94 2.4× 17 358
Rolf‐Rainer Grigat 171 2.1× 46 0.7× 24 0.4× 31 0.8× 42 1.1× 59 363
Bo Wu 35 0.4× 28 0.4× 11 0.2× 11 0.3× 20 0.5× 27 302
Harshit Gupta 35 0.4× 14 0.2× 38 0.6× 6 0.1× 47 1.2× 24 294
John Rasure 136 1.6× 21 0.3× 12 0.2× 20 0.5× 13 0.3× 15 360
Yu-Tai Ching 118 1.4× 31 0.5× 12 0.2× 28 0.7× 47 1.2× 38 341
Faysal Boughorbel 184 2.2× 6 0.1× 25 0.4× 38 0.9× 19 0.5× 15 316
Benoît Lelandais 33 0.4× 119 1.8× 38 0.6× 6 0.1× 55 1.4× 19 326

Countries citing papers authored by Federico Lecumberry

Since Specialization
Citations

This map shows the geographic impact of Federico Lecumberry'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 Lecumberry with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Federico Lecumberry more than expected).

Fields of papers citing papers by Federico Lecumberry

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Federico Lecumberry. 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 Lecumberry. The network helps show where Federico Lecumberry may publish in the future.

Co-authorship network of co-authors of Federico Lecumberry

This figure shows the co-authorship network connecting the top 25 collaborators of Federico Lecumberry. A scholar is included among the top collaborators of Federico Lecumberry 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 Lecumberry. Federico Lecumberry is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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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.

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