Daniel Berjón

499 citations
36 papers · 339 · h-index 11

Impact in

Papers in

Daniel Berjón

31 papers receiving 330 citations

Peers

Daniel Berjón
Comparison fields: 5 of 52
  • Computer Vision and Pattern Recognition 221
  • Computer Graphics and Computer-Aided Design 27
  • Media Technology 32
  • Human-Computer Interaction 17
  • Signal Processing 31
Replace Daesik Jang with:
Daesik Jang South Korea
Graeme A. Jones United Kingdom
Francisco Morán Spain
Daniel K. Du China
W. Niem Germany
Francesco Cricri Finland
J. Subrahmonia United States
Yufei Wang China
Daniel Berjón relative to Daesik Jang South Korea Daesik Jang's profile →
Citations per field
00.5×6.4×
Daesik Jang · 1×
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 23 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 36 papers — load more, or switch the sort, to bring in the rest.

#Work
1 201762
2 202051
3 202226
4 201326
5 201622
6 201221
7 201518
8 201415
9 201910
10 202410
11 201610
12 20239
13 20106
14 20155
15 20145
16 20125
17 20234
18 20234
19 20114
20 20224

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 36 papers that have together received 339 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 Enhancement Techniques (6 papers), Human Pose and Action Recognition (6 papers), Image and Video Quality Assessment (6 papers), Computer Graphics and Visualization 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 (221 citations), Computer Graphics and Computer-Aided Design (27 citations), Media Technology (32 citations), Human-Computer Interaction (17 citations) and Signal Processing (31 citations). Daniel Berjón has collaborated with scholars based in Spain, Switzerland and Italy. Frequent co-authors include Narciso Garcı́a, Francisco Morán, Carlos Cuevas, Fernando Jaureguizar, Carlos R. del‐Blanco, Raquel Martínez‐España, Javier Gismero Menoyo, A. Asensio‐López, Guillermo Gallego and Pablo Carballeira. Their work appears in journals such as Signal Processing Image Communication, IEEE Transactions on Consumer Electronics, Computer Graphics Forum, Sensors and Multimedia Tools and Applications.

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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