Massimo Martini

689 citations
13 papers · 447 indexed · 1 hit paper · h-index 8
Topics
3D Surveying and Cultural Heritage (6 papers)Remote Sensing and LiDAR Applications (6 papers)Archaeological Research and Protection (3 papers)
Journals
SHILAP Revista de lepidopterologíaIEEE AccessRemote Sensing
Partner nations
ItalySwitzerlandFrance

In The Last Decade

Massimo Martini

13 papers receiving 435 citations

Hit Papers

Point Cloud Semantic Segmentation Using a Deep Learning F...2020202620222024202050100150

Peers

Massimo Martini
Comparison fields: 5 of 63
  • Geology 324
  • Environmental Engineering 194
  • Computer Vision and Pattern Recognition 120
  • Conservation 88
  • Space and Planetary Science 79
Replace E. K. Stathopoulou with:
E. K. Stathopoulou Greece
Elisa Mariarosaria Farella Italy
José Herráez Spain
Maarten Bassier Belgium
Laura Loredana Micoli Italy
Laura Inzerillo Italy
Bashar Alsadik Netherlands
Sungchul Hong South Korea
Anđelo Martinović Belgium
Ali Hosseininaveh Ahmadabadian Iran
Massimo Martini relative to E. K. Stathopoulou Greece E. K. Stathopoulou's profile →
Citations per field
00.5×1.5×2.3×
E. K. Stathopoulou · 1×
Citations per year

Countries citing papers authored by Massimo Martini

Since Specialization
Citations

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

Fields of papers citing papers by Massimo Martini

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Massimo Martini

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

All Works

13 of 13 papers shown
#WorkIndexed citations
1 1
2 16
3 2
4 6
5 2
6 17
7 110
8
Point Cloud Semantic Segmentation Using a Deep Learning Framework for Cultural Heritagebreakdown →
183
9 17
10 6
11 51
12 26
13 10

About Massimo Martini

Massimo Martini is a scholar working on Space and Planetary Science, Geology and Environmental Engineering, having authored 13 papers that have together received 447 indexed citations. Recurring topics across this work include 3D Surveying and Cultural Heritage (6 papers), Remote Sensing and LiDAR Applications (6 papers) and Archaeological Research and Protection (3 papers). The work is most often cited by research in Space and Planetary Science (79 citations), Geology (324 citations) and Conservation (88 citations). Massimo Martini has collaborated with scholars based in Italy, Switzerland and France. Frequent co-authors include Marina Paolanti, Francesca Matrone, Roberto Pierdicca, Emanuele Frontoni, Eva Savina Malinverni, Christian Morbidoni, Andrea Maria Lingua, Eleonora Grilli, Fabio Remondino and Luca Romeo. Their work appears in journals such as SHILAP Revista de lepidopterología, IEEE Access and Remote Sensing.

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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