Koldo Basterretxea

663 citations
39 papers · 446 · h-index 12

Impact in

Papers in

Koldo Basterretxea

37 papers receiving 426 citations

Peers

Koldo Basterretxea
Comparison fields: 5 of 67
  • Artificial Intelligence 217
  • Computer Vision and Pattern Recognition 100
  • Hardware and Architecture 32
  • Control and Systems Engineering 88
  • Media Technology 32
Replace Javier Echanobe with:
Javier Echanobe Spain
Mukul Sutaone India
Guihe Qin China
S. Himavathi India
Mitra Mirhassani Canada
P. T. Vanathi India
Liang Zhou China
Leena Vachhani India
Fatih Erden United States
Shih‐An Li Taiwan
Koldo Basterretxea relative to Javier Echanobe Spain Javier Echanobe's profile →
Citations per field
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Javier Echanobe · 1×
Citations per year

Countries citing papers authored by Koldo Basterretxea

Since Specialization
Citations

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

Fields of papers citing papers by Koldo Basterretxea

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 8 scholars most cited alongside Koldo Basterretxea, 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 Koldo Basterretxea Line = papers co-authored together Koldo Basterretxea links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 39 papers — load more, or switch the sort, to bring in the rest.

#Work
1 200470
2 201537
3 200736
4 201332
5 200228
6 201425
7 200621
8 201120
9 202317
10 202116
11 201515
12 200213
13 201411
14 201211
15 202110
16 201110
17 20129
18 20167
19 20246
20 20236

About Koldo Basterretxea

Koldo Basterretxea is a scholar working on Artificial Intelligence, Control and Systems Engineering, Electrical and Electronic Engineering, Computer Vision and Pattern Recognition and Hardware and Architecture, having authored 39 papers that have together received 446 indexed citations. Recurring topics across this work include Fuzzy Logic and Control Systems (10 papers), Neural Networks and Applications (10 papers), Control Systems and Identification (7 papers), Advanced Memory and Neural Computing (7 papers), Machine Learning and ELM (6 papers), Fault Detection and Control Systems (5 papers), Context-Aware Activity Recognition Systems (4 papers) and Numerical Methods and Algorithms (4 papers). The work is most often cited by research in Artificial Intelligence (217 citations), Computer Vision and Pattern Recognition (100 citations), Hardware and Architecture (32 citations), Control and Systems Engineering (88 citations) and Media Technology (32 citations). Koldo Basterretxea has collaborated with scholars based in Spain and United Kingdom. Frequent co-authors include Javier Echanobe, I. del Campo, Faiyaz Doctor, V. Sanchez Martinez, Khaled Benkrid, Unai Ugalde, Rafael Bárcena and Eduardo Alonso. Their work appears in journals such as Electronics Letters, Journal of Systems Architecture, IEEE Transactions on Intelligent Transportation Systems, IEEE Transactions on Systems Man and Cybernetics Part B (Cybernetics) and Electronics.

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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