Javier Bernal

15 papers receiving 258 citations

Peers

Javier Bernal
Comparison fields: 5 of 96
  • Biophysics 50
  • Geology 21
  • Media Technology 29
  • Structural Biology 4
  • Geophysics 32
Replace Ilia V. Safonov with:
Ilia V. Safonov Russia
Feng Xue China
Pablo Musé France
Christophe Fiorio France
Shahid A. Haider Canada
Jack Perkins Australia
Rainer Stotzka Germany
David W. Paglieroni United States
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Citations per field
00.5×1.5×2.1×
Ilia V. Safonov · 1×
Citations per year

Countries citing papers authored by Javier Bernal

Since Specialization
Citations

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

Fields of papers citing papers by Javier Bernal

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside Javier Bernal, 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 Javier Bernal Line = papers co-authored together Javier Bernal links everyone, so they are left out of the graph.

All Works

16 of 16 papers shown
#Work
1 201178
2 200061
3 201525
4 200021
5 202120
6 200016
7 201914
8 20059
9 19838
10 20167
11 20156
12
Contour-to-grid interpolation with nonlinear finite elements : a feasibility study
19873
13
Synthetic Lung Tumor Data Sets for Comparison of Volumetric Algorithms.
20093
14 20152
15 20042
16
Non-Linear Contour-to-Grid Digital Interpolation,
19861

About Javier Bernal

Javier Bernal is a scholar working on Computer Vision and Pattern Recognition, Computational Mechanics, Artificial Intelligence, Computational Theory and Mathematics and Aerospace Engineering, having authored 16 papers that have together received 276 indexed citations. Recurring topics across this work include Image Processing and 3D Reconstruction (3 papers), Robotics and Sensor-Based Localization (2 papers), 3D Surveying and Cultural Heritage (2 papers), Advanced Numerical Analysis Techniques (2 papers), Computer Graphics and Visualization Techniques (2 papers), Vehicle Routing Optimization Methods (1 paper), Cell Image Analysis Techniques (1 paper) and Medical Imaging Techniques and Applications (1 paper). The work is most often cited by research in Biophysics (50 citations), Geology (21 citations), Media Technology (29 citations), Structural Biology (4 citations) and Geophysics (32 citations). Javier Bernal has collaborated with scholars based in United States, Spain and Egypt. Frequent co-authors include Christoph Witzgall, Andrés Riaguas, Antonio María Casas Sáinz, María Asunción Soriano, Adolfo Maestro, Michael Halter, Mary Brady, James J. Filliben, Anne L. Plant and John T. Elliott. Their work appears in journals such as Journal of Research of the National Institute of Standards and Technology, Information Sciences, Illinois Journal of Mathematics, Computers & Geosciences and Applied Mathematics Letters.

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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