Daniel Berjón

488 citations
33 papers · 328 · h-index 10

Impact in

Papers in

Daniel Berjón

31 papers receiving 319 citations

Peers

Daniel Berjón
Comparison fields: 5 of 52
  • Computer Vision and Pattern Recognition 219
  • Computer Graphics and Computer-Aided Design 25
  • Media Technology 33
  • Signal Processing 35
  • Human-Computer Interaction 15
Replace Jinhui Hu with:
Jinhui Hu China
Francisco Morán Spain
Daesik Jang South Korea
Kwon Junghyun South Korea
Graeme A. Jones United Kingdom
Francesco Cricri Finland
W. Niem Germany
Xinggang Lin China
Daniel Berjón relative to Jinhui Hu China Jinhui Hu's profile →
Citations per field
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Citations per year

Countries citing papers authored by Daniel Berjón

Since Specialization
Citations

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

Fields of papers citing papers by Daniel Berjón

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 19 scholars most cited alongside Daniel Berjón, 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 Daniel Berjón Line = papers co-authored together Daniel Berjón links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 33 papers — load more, or switch the sort, to bring in the rest.

#Work
1 201760
2 202048
3 201325
4 202224
5 202122
6 201622
7 201221
8 201517
9 201411
10 20199
11 20168
12 20106
13 20235
14 20155
15 20234
16 20234
17 20124
18 20114
19 20144
20
Optimal polygonal L1 linearization and fast interpolation of nonlinear systems
20143

About Daniel Berjón

Daniel Berjón is a scholar working on Computer Vision and Pattern Recognition, Computational Mechanics, Computer Graphics and Computer-Aided Design, Signal Processing and Aerospace Engineering, having authored 33 papers that have together received 328 indexed citations. Recurring topics across this work include Advanced Vision and Imaging (15 papers), Video Surveillance and Tracking Methods (11 papers), 3D Shape Modeling and Analysis (7 papers), Image and Video Quality Assessment (6 papers), Human Pose and Action Recognition (6 papers), Computer Graphics and Visualization Techniques (6 papers), Image Enhancement Techniques (6 papers) and Video Coding and Compression Technologies (5 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (219 citations), Computer Graphics and Computer-Aided Design (25 citations), Media Technology (33 citations), Signal Processing (35 citations) and Human-Computer Interaction (15 citations). Daniel Berjón has collaborated with scholars based in Spain, Switzerland and United States. Frequent co-authors include Narciso Garcı́a, Francisco Morán, Carlos Cuevas, Raquel Martínez‐España, Fernando Jaureguizar, Carlos R. del‐Blanco, Javier Gismero Menoyo, A. Asensio‐López, Guillermo Gallego and Julián Cabrera. Their work appears in journals such as Signal Processing Image Communication, IEEE Transactions on Consumer Electronics, Scientific Reports, IET Radar Sonar & Navigation and IEEE Transactions on Image Processing.

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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