Guillermo Botella

1.7k citations
116 papers · 1.2k · h-index 19

Impact in

Papers in

Guillermo Botella

108 papers receiving 1.2k citations

Peers

Guillermo Botella
Comparison fields: 5 of 92
  • Hardware and Architecture 186
  • Signal Processing 289
  • Computer Vision and Pattern Recognition 546
  • Media Technology 154
  • Computational Theory and Mathematics 175
Replace B.J. Falkowski with:
B.J. Falkowski Singapore
Uwe Meyer‐Baese United States
Mohsen Machhout Tunisia
Gagandeep Singh India
Viktor Öwall Sweden
Mário Véstias Portugal
Hyuk‐Jae Lee South Korea
Radomir S. Stanković Serbia
A. Venetsanopoulos Canada
Guillermo Botella relative to B.J. Falkowski Singapore B.J. Falkowski's profile →
Citations per field
00.5×3.8×
B.J. Falkowski · 1×
Citations per year

Countries citing papers authored by Guillermo Botella

Since Specialization
Citations

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

Fields of papers citing papers by Guillermo Botella

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 116 papers — load more, or switch the sort, to bring in the rest.

#Work
1 201893
2 200974
3 201354
4 201244
5 202042
6 201140
7 202234
8 202134
9 201232
10 201832
11 201231
12 201130
13 201330
14 202028
15 200828
16 201626
17 201221
18 201321
19 201518
20 202018

About Guillermo Botella

Guillermo Botella is a scholar working on Computer Vision and Pattern Recognition, Electrical and Electronic Engineering, Signal Processing, Artificial Intelligence and Hardware and Architecture, having authored 116 papers that have together received 1.2k indexed citations. Recurring topics across this work include Advanced Vision and Imaging (27 papers), Video Coding and Compression Technologies (22 papers), Numerical Methods and Algorithms (16 papers), Parallel Computing and Optimization Techniques (15 papers), Advanced Image Processing Techniques (14 papers), Low-power high-performance VLSI design (14 papers), CCD and CMOS Imaging Sensors (11 papers) and Embedded Systems Design Techniques (9 papers). The work is most often cited by research in Hardware and Architecture (186 citations), Signal Processing (289 citations), Computer Vision and Pattern Recognition (546 citations), Media Technology (154 citations) and Computational Theory and Mathematics (175 citations). Guillermo Botella has collaborated with scholars based in Spain, United States and Argentina. Frequent co-authors include Alberto A. Del Barrio, Carlos García, Manuel Prieto, Uwe Meyer‐Baese, Antonio García, Encarnación Castillo, Francisco Tirado, Eduardo Cabal‐Yépez, Marcelo Naiouf and Armando De Giusti. Their work appears in journals such as Digital Signal Processing, Computers & Electrical Engineering, Sensors, EPJ Quantum Technology and IEEE Transactions on Emerging Topics in Computing.

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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