Massimo Martini

699 citations
16 papers · 534 · 1 hit paper · h-index 9

Impact in

Papers in

Massimo Martini

16 papers receiving 514 citations

Massimo Martini's Hit Papers

Point Cloud Semantic Segmentation Using a Deep Learning Framework for Cultural Heritage 2020 · 211 citations
2110+2+4Years since publication50100150200

Peers

Massimo Martini
Comparison fields: 5 of 72
  • Space and Planetary Science 88
  • Geology 361
  • Conservation 96
  • Environmental Engineering 215
  • Computer Vision and Pattern Recognition 149
Replace E. K. Stathopoulou with:
E. K. Stathopoulou Greece
Laura Loredana Micoli Italy
Florent Poux Belgium
Maarten Bassier Belgium
Laura Inzerillo Italy
George Ioannakis Greece
Bashar Alsadik Netherlands
Pedro Martín Lerones Spain
Marina Khoroshiltseva Italy
Antonino Fotia Italy
Massimo Martini relative to E. K. Stathopoulou Greece E. K. Stathopoulou's profile →
Citations per field
00.5×1.6×
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-authors

The 20 scholars most cited alongside Massimo Martini, 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 Massimo Martini Line = papers co-authored together Massimo Martini links everyone, so they are left out of the graph.

All Works

16 of 16 papers shown
#Work
1
Point Cloud Semantic Segmentation Using a Deep Learning Framework for Cultural Heritage
Hit paper breakdown →
2020211
2 2020123
3 201959
4 201937
5 202121
6 202021
7 202219
8 201910
9 20199
10 20217
11 20226
12 20195
13 20222
14 20212
15 19951
16 20241

About Massimo Martini

Massimo Martini is a scholar working on Computer Vision and Pattern Recognition, Geology, Environmental Engineering, Artificial Intelligence and Space and Planetary Science, having authored 16 papers that have together received 534 indexed citations. Recurring topics across this work include 3D Surveying and Cultural Heritage (7 papers), Remote Sensing and LiDAR Applications (6 papers), Archaeological Research and Protection (3 papers), Industrial Vision Systems and Defect Detection (3 papers), Advanced Image and Video Retrieval Techniques (3 papers), Sentiment Analysis and Opinion Mining (2 papers), Visual Attention and Saliency Detection (2 papers) and Video Surveillance and Tracking Methods (2 papers). The work is most often cited by research in Space and Planetary Science (88 citations), Geology (361 citations), Conservation (96 citations), Environmental Engineering (215 citations) and Computer Vision and Pattern Recognition (149 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, Fabio Remondino, Eleonora Grilli and Primo Zingaretti. Their work appears in journals such as Remote Sensing, Virtual Archaeology Review, Pattern Recognition Letters, IEEE Access and IEEE Journal of Selected Topics in Applied Earth Observations 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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