Gregorio Bernabé

495 citations
47 papers · 340 · h-index 11

Impact in

Papers in

Gregorio Bernabé

41 papers receiving 327 citations

Peers

Gregorio Bernabé
Comparison fields: 5 of 71
  • Computer Vision and Pattern Recognition 184
  • Signal Processing 73
  • Media Technology 39
  • Hardware and Architecture 28
  • Cardiology and Cardiovascular Medicine 47
Replace S. Chandrasekaran with:
S. Chandrasekaran United Kingdom
Sandeep Kakde India
Mateus Grellert Brazil
Karri Chiranjeevi India
Khalid Tahboub United States
Quentin Duval Germany
Chongzhi Zhang China
Jamil Al-Azzeh Jordan
M. P. Pavan Kumar India
Selma Boumerdassi France
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Citations per field
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S. Chandrasekaran · 1×
Citations per year

Countries citing papers authored by Gregorio Bernabé

Since Specialization
Citations

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

Fields of papers citing papers by Gregorio Bernabé

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 24 scholars most cited alongside Gregorio Bernabé, 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 Gregorio Bernabé Line = papers co-authored together Gregorio Bernabé links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 47 papers — load more, or switch the sort, to bring in the rest.

#Work
1 200966
2 202229
3 201028
4 200222
5 201120
6 200813
7 202112
8 201312
9 200311
10 200510
11 201410
12 20158
13 20188
14 20207
15 20037
16 20037
17 20167
18 20067
19 20156
20 20125

About Gregorio Bernabé

Gregorio Bernabé is a scholar working on Computer Vision and Pattern Recognition, Cardiology and Cardiovascular Medicine, Hardware and Architecture, Computer Networks and Communications and Signal Processing, having authored 47 papers that have together received 340 indexed citations. Recurring topics across this work include Advanced Data Compression Techniques (16 papers), Image and Signal Denoising Methods (15 papers), Cardiomyopathy and Myosin Studies (11 papers), Parallel Computing and Optimization Techniques (7 papers), Cardiovascular Function and Risk Factors (7 papers), Image Enhancement Techniques (4 papers), Advanced Image Fusion Techniques (4 papers) and Digital Filter Design and Implementation (3 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (184 citations), Signal Processing (73 citations), Media Technology (39 citations), Hardware and Architecture (28 citations) and Cardiology and Cardiovascular Medicine (47 citations). Gregorio Bernabé has collaborated with scholars based in Spain, Colombia and Italy. Frequent co-authors include Juan Fernández, José M. Garcı́a, Manuel E. Acacio, Javier Cuenca, Domingo Giménez, Manuel Ujaldón, Jesús González, Josefa González‐Carrillo, José González and J. Duato. Their work appears in journals such as Journal of Clinical Medicine, Berichte aus der medizinischen Informatik und Bioinformatik/Journal of integrative bioinformatics, Computer Methods and Programs in Biomedicine, Parallel Computing and Journal of Systems and Software.

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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