Daniel Chaver

406 citations
38 papers · 298 · h-index 11

Impact in

Papers in

Daniel Chaver

35 papers receiving 288 citations

Peers

Daniel Chaver
Comparison fields: 5 of 33
  • Hardware and Architecture 201
  • Computer Networks and Communications 156
  • Computer Vision and Pattern Recognition 76
  • Media Technology 28
  • Signal Processing 31
Replace N.L. Passos with:
N.L. Passos United States
Thomas Unterluggauer Austria
Emil Matúš Germany
José González Spain
Edson Lemos Horta Brazil
Ayaz Akram United States
Mario Werner Austria
Graham Schelle United States
Naraig Manjikian Canada
Christophe Wolinski France
Daniel Chaver relative to N.L. Passos United States N.L. Passos's profile →
Citations per field
00.5×12×
N.L. Passos · 1×
Citations per year

Countries citing papers authored by Daniel Chaver

Since Specialization
Citations

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

Fields of papers citing papers by Daniel Chaver

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 38 papers — load more, or switch the sort, to bring in the rest.

#Work
1 200335
2 200425
3 200223
4 200221
5 201620
6 200319
7 200314
8 201313
9 202113
10 201712
11 201510
12 20038
13 20148
14 20067
15 20067
16 20146
17 20116
18 20066
19 20154
20 20054

About Daniel Chaver

Daniel Chaver is a scholar working on Hardware and Architecture, Computer Networks and Communications, Electrical and Electronic Engineering, Media Technology and Computer Vision and Pattern Recognition, having authored 38 papers that have together received 298 indexed citations. Recurring topics across this work include Parallel Computing and Optimization Techniques (27 papers), Advanced Data Storage Technologies (17 papers), Interconnection Networks and Systems (13 papers), Embedded Systems Design Techniques (8 papers), Advanced Memory and Neural Computing (5 papers), Image and Signal Denoising Methods (4 papers), Medical Image Segmentation Techniques (3 papers) and Experimental Learning in Engineering (3 papers). The work is most often cited by research in Hardware and Architecture (201 citations), Computer Networks and Communications (156 citations), Computer Vision and Pattern Recognition (76 citations), Media Technology (28 citations) and Signal Processing (31 citations). Daniel Chaver has collaborated with scholars based in Spain, United States and Argentina. Frequent co-authors include Manuel Prieto, Luís Piñuel, Francisco Tirado, Michael Huang, Christian Tenllado, Juan Carlos Sáez, José Ignacio Gómez, Sarah Harris, F. Castro and David Harris. Their work appears in journals such as The Computer Journal, IEEE Micro, Journal of Systems Architecture, Journal of Parallel and Distributed Computing and International journal of engineering education.

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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