Simone Melzi

2.9k citations
37 papers · 874 indexed · h-index 14

Impact in

Papers in

Simone Melzi

34 papers receiving 846 citations

Peers

Simone Melzi
Comparison fields: 5 of 100
  • Computer Graphics and Computer-Aided Design 178
  • Computer Vision and Pattern Recognition 449
  • Computational Mechanics 413
  • Geology 65
  • Artificial Intelligence 209
Replace Pere‐Pau Vázquez with:
Pere‐Pau Vázquez Spain
Ali Thabet Saudi Arabia
Lee M. Seversky United States
Mathieu Aubry France
Shuyang Gu China
Hao Zhao China
Carlos Hernández Mexico
Bo Dai China
Yibing Zhan China
Oliver J. Woodford United Kingdom
Simone Melzi relative to Pere‐Pau Vázquez Spain Pere‐Pau Vázquez's profile →
Citations per field
00.5×3.5×
Pere‐Pau Vázquez · 1×
Citations per year

Countries citing papers authored by Simone Melzi

Since Specialization
Citations

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

Fields of papers citing papers by Simone Melzi

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 37 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2015221
2 2020136
3 2015124
4 201984
5 202035
6 201828
7 202024
8 202123
9 202021
10 202217
11 201917
12 201814
13 201914
14 201613
15 202012
16 201611
17 202011
18
Feature Selection via Eigenvector Centrality
201610
19 202110
20 20217

About Simone Melzi

Simone Melzi is a scholar working on Computational Mechanics, Computer Vision and Pattern Recognition, Computer Graphics and Computer-Aided Design, Artificial Intelligence and Geology, having authored 37 papers that have together received 874 indexed citations. Recurring topics across this work include 3D Shape Modeling and Analysis (24 papers), Computer Graphics and Visualization Techniques (15 papers), Advanced Numerical Analysis Techniques (8 papers), Image Processing and 3D Reconstruction (7 papers), Advanced Vision and Imaging (5 papers), Human Pose and Action Recognition (4 papers), Face and Expression Recognition (3 papers) and 3D Surveying and Cultural Heritage (3 papers). The work is most often cited by research in Computer Graphics and Computer-Aided Design (178 citations), Computer Vision and Pattern Recognition (449 citations), Computational Mechanics (413 citations), Geology (65 citations) and Artificial Intelligence (209 citations). Simone Melzi has collaborated with scholars based in Italy, France and United Kingdom. Frequent co-authors include Giorgio Roffo, Marco Cristani, Umberto Castellani, Michael M. Bronstein, Maks Ovsjanikov, Emanuele Rodolà, Peter Wonka, Jing Ren, Alessandro Vinciarelli and Jonathan Masci. Their work appears in journals such as Computer Graphics Forum, Computers & Graphics, ACM Transactions on Graphics, Frontiers in Pediatrics and International Journal of Computer Vision.

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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