Diego Macrini

792 citations
18 papers · 611 · h-index 11

Impact in

Papers in

Diego Macrini

18 papers receiving 585 citations

Peers

Diego Macrini
Comparison fields: 5 of 52
  • Computer Vision and Pattern Recognition 528
  • Computer Graphics and Computer-Aided Design 82
  • Computational Mechanics 249
  • Geology 37
  • Signal Processing 43
Replace Roee Litman with:
Roee Litman Israel
Leonidas Guibas United States
G. Guy United States
Artiom Kovnatsky Switzerland
Yonathan Aflalo Israel
C. Rothwell United Kingdom
Y. Lamdan United States
Chahab Nastar France
Ulrich Schlickewei Germany
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Citations per field
00.5×1.7×
Roee Litman · 1×
Citations per year

Countries citing papers authored by Diego Macrini

Since Specialization
Citations

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

Fields of papers citing papers by Diego Macrini

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 18 scholars most cited alongside Diego Macrini, 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 Diego Macrini Line = papers co-authored together Diego Macrini links everyone, so they are left out of the graph.

All Works

18 of 18 papers shown
#Work
1 2007199
2 2005111
3 200552
4 200847
5 200339
6 200636
7 200628
8 201127
9 201122
10 201218
11
Indexing and Matching for View-Based 3-D Object Recognition Using Shock Graphs
200314
12 20067
13 20083
14 20112
15
The Current State and TRL Assessment of People Tracking Technology for Video Surveillance Applications
20142
16 20052
17
A Computer Vision System for Spaceborne Safety Monitoring
20051
18 20021

About Diego Macrini

Diego Macrini is a scholar working on Computer Vision and Pattern Recognition, Computational Mechanics, Aerospace Engineering, Signal Processing and Artificial Intelligence, having authored 18 papers that have together received 611 indexed citations. Recurring topics across this work include Advanced Image and Video Retrieval Techniques (12 papers), Graph Theory and Algorithms (9 papers), Image Processing and 3D Reconstruction (5 papers), Image Retrieval and Classification Techniques (4 papers), 3D Shape Modeling and Analysis (4 papers), Medical Image Segmentation Techniques (3 papers), Data Management and Algorithms (2 papers) and Advanced Graph Neural Networks (2 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (528 citations), Computer Graphics and Computer-Aided Design (82 citations), Computational Mechanics (249 citations), Geology (37 citations) and Signal Processing (43 citations). Diego Macrini has collaborated with scholars based in Canada, United States and Sweden. Frequent co-authors include Sven Dickinson, Kaleem Siddiqi, Ali Shokoufandeh, Juan Zhang, Sylvain Bouix, Steven W. Zucker, David J. Fleet, Juan Zhang, M. Fatih Demirci and Matthijs van Eede. Their work appears in journals such as Computer Vision and Image Understanding, Machine Vision and Applications, IEEE Transactions on Pattern Analysis and Machine Intelligence, Lecture notes in computer science and IET 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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