Javier Díaz

2.4k citations
102 papers · 1.6k · h-index 20

Impact in

Papers in

Javier Díaz

97 papers receiving 1.5k citations

Peers

Javier Díaz
Comparison fields: 5 of 116
  • Computer Vision and Pattern Recognition 710
  • Hardware and Architecture 162
  • Media Technology 181
  • Computer Networks and Communications 377
  • Aerospace Engineering 213
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Yuhao Zhu United States
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Richard Weiss United States
Markus Steinberger Austria
Nikos Chrisochoides United States
Witold Kinsner Canada
Miriam Leeser United States
Cheng Liu China
Pedro V. Sander United States
Yuzhen Niu China
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Citations per field
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Citations per year

Countries citing papers authored by Javier Díaz

Since Specialization
Citations

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

Fields of papers citing papers by Javier Díaz

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 102 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2012160
2 2006134
3 2011103
4 201267
5 201359
6 201158
7 200656
8 201355
9 200851
10 200945
11 200842
12 200337
13 201328
14 201028
15 200927
16 201224
17 201024
18 200921
19 201120
20 200720

About Javier Díaz

Javier Díaz is a scholar working on Computer Vision and Pattern Recognition, Electrical and Electronic Engineering, Computer Networks and Communications, Media Technology and Aerospace Engineering, having authored 102 papers that have together received 1.6k indexed citations. Recurring topics across this work include Advanced Vision and Imaging (36 papers), Network Time Synchronization Technologies (21 papers), Image Processing Techniques and Applications (18 papers), CCD and CMOS Imaging Sensors (14 papers), Advancements in PLL and VCO Technologies (12 papers), Advanced Image Processing Techniques (10 papers), Advanced Image and Video Retrieval Techniques (9 papers) and Distributed and Parallel Computing Systems (9 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (710 citations), Hardware and Architecture (162 citations), Media Technology (181 citations), Computer Networks and Communications (377 citations) and Aerospace Engineering (213 citations). Javier Díaz has collaborated with scholars based in Spain, United States and Italy. Frequent co-authors include Eduardo Ros, Camelia Muñoz‐Caro, Alfonso Niño, Sonia Mota, Matteo Tomasi, Eva M. Ortigosa, Karl Pauwels, Francisco Barranco, Francisco Pelayo and Mauricio Vanegas. Their work appears in journals such as IEEE Transactions on Industrial Informatics, Machine Vision and Applications, Fusion Engineering and Design, Sensors and IEEE Access.

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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