F. Vaz

495 citations
21 papers · 381 · h-index 10

Impact in

Papers in

F. Vaz

17 papers receiving 357 citations

Peers

F. Vaz
Comparison fields: 5 of 60
  • Cellular and Molecular Neuroscience 111
  • Geology 30
  • Biomedical Engineering 200
  • Computer Vision and Pattern Recognition 76
  • Cardiology and Cardiovascular Medicine 61
Replace Ji-Hoon Kim with:
Ji-Hoon Kim South Korea
Wolfgang Sepp Germany
Atsunori Kanemura Japan
Beanbonyka Rim South Korea
Hannes Gamper United States
Zhenghao Shi China
Beate Meffert Germany
Feifei Qi China
F. Vaz relative to Ji-Hoon Kim South Korea Ji-Hoon Kim's profile →
Citations per field
00.5×2×3×4.3×
Ji-Hoon Kim · 1×
Citations per year

Countries citing papers authored by F. Vaz

Since Specialization
Citations

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

Fields of papers citing papers by F. Vaz

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 13 scholars most cited alongside F. Vaz, 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 F. Vaz Line = papers co-authored together F. Vaz links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 21 papers — load more, or switch the sort, to bring in the rest.

#Work
1 1998107
2 200297
3 200434
4 200223
5 200116
6 200216
7 199916
8 200414
9
INFLUENCE OF DYNAMICS IN THE PERCEIVED NATURALNESS OF PORTUGUESE NASAL VOWELS
199914
10 200210
11 20059
12 20058
13 20047
14 20024
15 20023
16 20052
17 20021
18 20020
19 20020
20
Reconhecimento do orador com redes neuronais
19940

About F. Vaz

F. Vaz is a scholar working on Signal Processing, Computer Vision and Pattern Recognition, Experimental and Cognitive Psychology, Artificial Intelligence and Cognitive Neuroscience, having authored 21 papers that have together received 381 indexed citations. Recurring topics across this work include EEG and Brain-Computer Interfaces (4 papers), Advanced Vision and Imaging (4 papers), Blind Source Separation Techniques (4 papers), Robotics and Sensor-Based Localization (4 papers), Speech and Audio Processing (4 papers), Speech Recognition and Synthesis (4 papers), Optical measurement and interference techniques (4 papers) and Phonetics and Phonology Research (4 papers). The work is most often cited by research in Cellular and Molecular Neuroscience (111 citations), Geology (30 citations), Biomedical Engineering (200 citations), Computer Vision and Pattern Recognition (76 citations) and Cardiology and Cardiovascular Medicine (61 citations). F. Vaz has collaborated with scholars based in Portugal, Italy and United Kingdom. Frequent co-authors include Rui Escadas Martins, S. Selberherr, J.G.M. Gonçalves, Paulo Dias, V. Sequeira, António Teixeira, Carlos A. C. Bastos, P.J. Fish, Vitor M. F. Santos and José Carlos Príncipe. Their work appears in journals such as Robotics and Autonomous Systems, IEEE Transactions on Instrumentation and Measurement, IEEE Transactions on Ultrasonics Ferroelectrics and Frequency Control, Portuguese National Funding Agency for Science, Research and Technology (RCAAP Project by FCT) and Defense Technical Information Center (DTIC).

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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