Lucas Veronese

28 total papers · 462 total citations
16 papers, 276 citations indexed

About

Lucas Veronese is a scholar working on Computer Vision and Pattern Recognition, Aerospace Engineering and Artificial Intelligence. According to data from OpenAlex, Lucas Veronese has authored 16 papers receiving a total of 276 indexed citations (citations by other indexed papers that have themselves been cited), including 9 papers in Computer Vision and Pattern Recognition, 7 papers in Aerospace Engineering and 6 papers in Artificial Intelligence. Recurrent topics in Lucas Veronese's work include Robotics and Sensor-Based Localization (7 papers), Remote Sensing and LiDAR Applications (5 papers) and Indoor and Outdoor Localization Technologies (4 papers). Lucas Veronese is often cited by papers focused on Robotics and Sensor-Based Localization (7 papers), Remote Sensing and LiDAR Applications (5 papers) and Indoor and Outdoor Localization Technologies (4 papers). Lucas Veronese collaborates with scholars based in Brazil, Chile and Australia. Lucas Veronese's co-authors include Renato A. Krohling, Alberto F. De Souza, Claudine Badué, Fernando Auat Cheein, José Guivant, Thiago Oliveira-Santos, Edilson de Aguiar, Patrick Marques Ciarelli, Elias Oliveira and Mathias Schulze and has published in prestigious journals such as IEEE Transactions on Intelligent Transportation Systems, Neurocomputing and Journal of Field Robotics.

In The Last Decade

Lucas Veronese

16 papers receiving 254 citations

Author Peers

Peers are selected by citation overlap in the author's most active subfields. citations · hero ref

Author Last Decade Papers Cites
Lucas Veronese 121 90 73 46 45 16 276
Youcheng Zhang 110 0.9× 86 1.0× 24 0.3× 92 2.0× 48 1.1× 17 285
Tarik Nahhal 68 0.6× 66 0.7× 42 0.6× 11 0.2× 32 0.7× 18 297
Shengwei Fu 146 1.2× 88 1.0× 54 0.7× 13 0.3× 22 0.5× 16 265
Yang Gu 133 1.1× 77 0.9× 59 0.8× 24 0.5× 88 2.0× 20 325
Noorzaily Mohamed Noor 63 0.5× 81 0.9× 144 2.0× 13 0.3× 95 2.1× 16 330
Vassilios Petridis 175 1.4× 77 0.9× 27 0.4× 8 0.2× 29 0.6× 17 305
Zhenglei Wei 230 1.9× 51 0.6× 57 0.8× 11 0.2× 46 1.0× 30 322
Ali Ghanbari Sorkhi 53 0.4× 78 0.9× 24 0.3× 36 0.8× 8 0.2× 21 206
EL Dagless 44 0.4× 141 1.6× 23 0.3× 33 0.7× 47 1.0× 23 312
Bin Zhang 63 0.5× 76 0.8× 15 0.2× 19 0.4× 60 1.3× 13 317

Countries citing papers authored by Lucas Veronese

Since Specialization
Citations

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

Fields of papers citing papers by Lucas Veronese

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Lucas Veronese

This figure shows the co-authorship network connecting the top 25 collaborators of Lucas Veronese. A scholar is included among the top collaborators of Lucas Veronese 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 Lucas Veronese. Lucas Veronese is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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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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