Daniel Díaz-Sánchez

1.2k citations
67 papers · 773 · h-index 12

Impact in

Papers in

Daniel Díaz-Sánchez

60 papers receiving 736 citations

Peers

Daniel Díaz-Sánchez
Comparison fields: 5 of 85
  • Computer Networks and Communications 382
  • Information Systems 307
  • Computer Vision and Pattern Recognition 164
  • Signal Processing 72
  • Media Technology 50
Replace Karel Wouters with:
Karel Wouters Belgium
Biao Song Saudi Arabia
Muhammad Usman Shahid Khan Pakistan
Fang−Yie Leu Taiwan
François Carrez United Kingdom
Oleksiy Mazhelis Finland
Yeh-Cheng Chen United States
Niko Mäkitalo Finland
Mário A. R. Dantas Brazil
Badis Hammi France
Daniel Díaz-Sánchez relative to Karel Wouters Belgium Karel Wouters's profile →
Citations per field
00.5×6.8×
Karel Wouters · 1×
Citations per year

Countries citing papers authored by Daniel Díaz-Sánchez

Since Specialization
Citations

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

Fields of papers citing papers by Daniel Díaz-Sánchez

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 67 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2016239
2 201160
3 201250
4 201740
5 201932
6 201727
7 201226
8 200918
9 201117
10 201216
11 201312
12 201912
13 201511
14 201610
15 201910
16 201610
17 20159
18 20138
19 20068
20 20208

About Daniel Díaz-Sánchez

Daniel Díaz-Sánchez is a scholar working on Computer Networks and Communications, Information Systems, Computer Vision and Pattern Recognition, Sociology and Political Science and Artificial Intelligence, having authored 67 papers that have together received 773 indexed citations. Recurring topics across this work include IoT and Edge/Fog Computing (16 papers), Caching and Content Delivery (14 papers), Context-Aware Activity Recognition Systems (13 papers), Multimedia Communication and Technology (9 papers), Cloud Data Security Solutions (9 papers), Cryptography and Data Security (8 papers), Access Control and Trust (7 papers) and Advanced Data Storage Technologies (7 papers). The work is most often cited by research in Computer Networks and Communications (382 citations), Information Systems (307 citations), Computer Vision and Pattern Recognition (164 citations), Signal Processing (72 citations) and Media Technology (50 citations). Daniel Díaz-Sánchez has collaborated with scholars based in Spain, United Kingdom and Germany. Frequent co-authors include Andrés Marín, R. Simon Sherratt, Terence Hui, Patricia Arias-Cabarcos, Florina Almenárez, Davide Proserpio, Carlos García-Rubio, Celeste Campo, Rosa María Galán Sánchez and Rubén Trapero. Their work appears in journals such as IEEE Transactions on Consumer Electronics, Computer Networks, Electronics, Future Generation Computer Systems and Sensors.

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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