Lapo Governi

194 total papers · 2.2k total citations
112 papers, 1.3k citations indexed

About

Lapo Governi is a scholar working on Computer Vision and Pattern Recognition, Biomedical Engineering and Industrial and Manufacturing Engineering. According to data from OpenAlex, Lapo Governi has authored 112 papers receiving a total of 1.3k indexed citations (citations by other indexed papers that have themselves been cited), including 27 papers in Computer Vision and Pattern Recognition, 24 papers in Biomedical Engineering and 24 papers in Industrial and Manufacturing Engineering. Recurrent topics in Lapo Governi's work include 3D Surveying and Cultural Heritage (20 papers), Industrial Vision Systems and Defect Detection (13 papers) and Optical measurement and interference techniques (12 papers). Lapo Governi is often cited by papers focused on 3D Surveying and Cultural Heritage (20 papers), Industrial Vision Systems and Defect Detection (13 papers) and Optical measurement and interference techniques (12 papers). Lapo Governi collaborates with scholars based in Italy, Netherlands and Spain. Lapo Governi's co-authors include Rocco Furferi, Yary Volpe, Monica Carfagni, Francesco Buonamici, Francesca Uccheddu, Michaela Servi, Alessandro Lapini, Kathleen S. McGreevy, Alessandro Ridolfi and Enrico Meli and has published in prestigious journals such as SHILAP Revista de lepidopterología, The Journal of the Acoustical Society of America and Sensors.

In The Last Decade

Lapo Governi

104 papers receiving 1.2k citations

Author Peers

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

Author Last Decade Papers Cites
Lapo Governi 304 303 277 188 173 112 1.3k
Rocco Furferi 336 1.1× 318 1.0× 329 1.2× 216 1.1× 185 1.1× 136 1.5k
Yary Volpe 299 1.0× 369 1.2× 239 0.9× 180 1.0× 180 1.0× 130 1.4k
Tsz-Ho Kwok 249 0.8× 268 0.9× 244 0.9× 404 2.1× 83 0.5× 79 1.5k
Caterina Rizzi 124 0.4× 309 1.0× 206 0.7× 173 0.9× 34 0.2× 128 1.1k
Armando Viviano Razionale 500 1.6× 227 0.7× 95 0.3× 193 1.0× 230 1.3× 73 1.5k
Nobuyuki Umetani 377 1.2× 83 0.3× 163 0.6× 185 1.0× 89 0.5× 47 1.3k
Giuseppe Monno 403 1.3× 355 1.2× 99 0.4× 262 1.4× 54 0.3× 48 1.4k
Ning Dai 221 0.7× 350 1.2× 146 0.5× 627 3.3× 46 0.3× 112 1.7k
Jun Mitani 771 2.5× 150 0.5× 120 0.4× 345 1.8× 132 0.8× 100 1.7k
Luigi Maria Galantucci 253 0.8× 355 1.2× 605 2.2× 833 4.4× 216 1.2× 87 1.8k

Countries citing papers authored by Lapo Governi

Since Specialization
Citations

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

Fields of papers citing papers by Lapo Governi

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Lapo Governi

This figure shows the co-authorship network connecting the top 25 collaborators of Lapo Governi. A scholar is included among the top collaborators of Lapo Governi 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 Lapo Governi. Lapo Governi 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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2026