V. Sequeira

1.1k citations
63 papers · 715 · h-index 15

Impact in

Papers in

V. Sequeira

59 papers receiving 650 citations

Peers

V. Sequeira
Comparison fields: 5 of 84
  • Geology 327
  • Computer Vision and Pattern Recognition 358
  • Aerospace Engineering 389
  • Computer Graphics and Computer-Aided Design 56
  • Environmental Engineering 202
Replace J.G.M. Gonçalves with:
J.G.M. Gonçalves Italy
François Blais Canada
S.W. Lee South Korea
Pierre Moulon France
Carles Matabosch Spain
Timothy A. Clarke United Kingdom
Réjean Baribeau Canada
Bernhard P. Wrobel Germany
Rasmus Ramsbøl Jensen Denmark
Jan Tops Belgium
V. Sequeira relative to J.G.M. Gonçalves Italy J.G.M. Gonçalves's profile →
Citations per field
00.5×5.3×
J.G.M. Gonçalves · 1×
Citations per year

Countries citing papers authored by V. Sequeira

Since Specialization
Citations

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

Fields of papers citing papers by V. Sequeira

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 63 papers — load more, or switch the sort, to bring in the rest.

#Work
1 1999139
2 199846
3 200337
4 200437
5 201032
6 201529
7 199529
8 200725
9 199624
10 200223
11 200221
12 200520
13 200018
14 201617
15 200414
16 201914
17 200714
18 200013
19 200012
20 200811

About V. Sequeira

V. Sequeira is a scholar working on Aerospace Engineering, Computer Vision and Pattern Recognition, Geology, Environmental Engineering and Biomedical Engineering, having authored 63 papers that have together received 715 indexed citations. Recurring topics across this work include Robotics and Sensor-Based Localization (36 papers), 3D Surveying and Cultural Heritage (27 papers), Advanced Vision and Imaging (23 papers), Remote Sensing and LiDAR Applications (11 papers), Optical measurement and interference techniques (9 papers), Advanced X-ray and CT Imaging (5 papers), Image and Object Detection Techniques (5 papers) and Nuclear Physics and Applications (5 papers). The work is most often cited by research in Geology (327 citations), Computer Vision and Pattern Recognition (358 citations), Aerospace Engineering (389 citations), Computer Graphics and Computer-Aided Design (56 citations) and Environmental Engineering (202 citations). V. Sequeira has collaborated with scholars based in Italy, Belgium and Portugal. Frequent co-authors include J.G.M. Gonçalves, David Hogg, Isabel Ribeiro, Paulo Dias, F. Vaz, Konrad Klein, Jian Yao, Kia Ng, Paolo Peerani and Maurizio Teobaldelli. Their work appears in journals such as Robotics and Autonomous Systems, ISPRS Journal of Photogrammetry and Remote Sensing, Machine Vision and Applications, The International Journal of Robotics Research and Nuclear Instruments and Methods in Physics Research Section B Beam Interactions with Materials and Atoms.

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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