Paulo Peixoto

1.6k citations
50 papers · 1.1k indexed · h-index 15
Topics
Advanced Vision and Imaging (14 papers)Robotics and Sensor-Based Localization (14 papers)Autonomous Vehicle Technology and Safety (10 papers)

In The Last Decade

Paulo Peixoto

47 papers receiving 1.0k citations

Peers

Paulo Peixoto
Comparison fields: 5 of 94
  • Computer Vision and Pattern Recognition 663
  • Automotive Engineering 349
  • Aerospace Engineering 269
  • Environmental Engineering 239
  • Artificial Intelligence 149
Replace Cristiano Premebida with:
Cristiano Premebida Portugal
Ashesh Jain United States
W.S. Wijesoma Singapore
Guangming Xiong China
Julian F. P. Kooij Netherlands
Ming-Fang Chang Taiwan
Jianhui Zhao China
Luciano Spinello Germany
Ankit A. Ravankar Japan
Paulo Peixoto relative to Cristiano Premebida Portugal Cristiano Premebida's profile →
Citations per field
00.5×1.5×
Cristiano Premebida · 1×
Citations per year

Countries citing papers authored by Paulo Peixoto

Since Specialization
Citations

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

Fields of papers citing papers by Paulo Peixoto

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Paulo Peixoto

This figure shows the co-authorship network connecting the top 25 collaborators of Paulo Peixoto. A scholar is included among the top collaborators of Paulo Peixoto based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Paulo Peixoto. Paulo Peixoto is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
#WorkIndexed citations
1 6
2 1
3 1
4 18
5 4
6 10
7 5
8 10
9 44
10 161
11 14
12 60
13 5
14 7
15 29
16 43
17 2
18 4
19 7
20 25

About Paulo Peixoto

Paulo Peixoto is a scholar working on Computer Vision and Pattern Recognition, Media Technology and Automotive Engineering, having authored 50 papers that have together received 1.1k indexed citations. Recurring topics across this work include Advanced Vision and Imaging (14 papers), Robotics and Sensor-Based Localization (14 papers) and Autonomous Vehicle Technology and Safety (10 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (663 citations), Automotive Engineering (349 citations) and Instrumentation (75 citations). Paulo Peixoto has collaborated with scholars based in Portugal, United Kingdom and United Arab Emirates. Frequent co-authors include Urbano Nunes, Cristiano Premebida, Alireza Asvadi, Luís Garrote, Jorge Batista, João Paulo, Hélder Araújo, Luciano Oliveira, Diego R. Faria and Rui Fernandes. Their work appears in journals such as Advanced Functional Materials, Sensors and Pattern Recognition.

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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