Pedro Real

66 papers receiving 553 citations

Peers

Pedro Real
Comparison fields: 5 of 98
  • Mathematical Physics 117
  • Computational Theory and Mathematics 201
  • Geometry and Topology 73
  • Algebra and Number Theory 36
  • Computer Vision and Pattern Recognition 125
Replace Frédéric Jean with:
Frédéric Jean France
Bart Braden United States
Heinrich Werner Germany
Nihar Kumar Mahato India
Yingkun Li China
Sebastian Kurtek United States
Daniel Fritsch United States
Mario Hlawitschka Germany
Michael J. Johnson Kuwait
Chinmaya Panigrahy India
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Countries citing papers authored by Pedro Real

Since Specialization
Citations

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

Fields of papers citing papers by Pedro Real

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside Pedro Real, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Pedro Real Line = papers co-authored together Pedro Real links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 75 papers — load more, or switch the sort, to bring in the rest.

#Work
1 201554
2 201647
3 201945
4 200436
5 201128
6 200925
7 200225
8 200024
9 200319
10 199917
11 201016
12 202315
13 200814
14 201314
15 200812
16 199011
17 201011
18 200811
19 201210
20 201110

About Pedro Real

Pedro Real is a scholar working on Computational Theory and Mathematics, Computer Vision and Pattern Recognition, Mathematical Physics, Geometry and Topology and Molecular Biology, having authored 75 papers that have together received 603 indexed citations. Recurring topics across this work include Topological and Geometric Data Analysis (27 papers), Homotopy and Cohomology in Algebraic Topology (21 papers), Digital Image Processing Techniques (17 papers), Algebraic structures and combinatorial models (9 papers), DNA and Biological Computing (9 papers), Advanced Topics in Algebra (9 papers), Cellular Automata and Applications (7 papers) and Medical Image Segmentation Techniques (5 papers). The work is most often cited by research in Mathematical Physics (117 citations), Computational Theory and Mathematics (201 citations), Geometry and Topology (73 citations), Algebra and Number Theory (36 citations) and Computer Vision and Pattern Recognition (125 citations). Pedro Real has collaborated with scholars based in Spain, France and Austria. Frequent co-authors include Rocı́o González-Dı́az, Daniel Díaz-Pernil, Helena Molina‐Abril, Rolando Rodrı́guez, Miguel Á. Gutiérrez-Naranjo, Antonio Oliviero, Vanesa Soto-León, Guglielmo Foffani, Víctor Álvarez and Bryan A. Strange. Their work appears in journals such as Pattern Recognition Letters, Homology Homotopy and Applications, Discrete Applied Mathematics, Sensors and Mathematical and Computer Modelling.

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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