Federico Magistri

820 citations
32 papers · 492 indexed · h-index 14
Topics
Smart Agriculture and AI (23 papers)Remote Sensing and LiDAR Applications (9 papers)Remote Sensing in Agriculture (7 papers)

In The Last Decade

Federico Magistri

30 papers receiving 474 citations

Peers

Federico Magistri
Comparison fields: 5 of 58
  • Plant Science 324
  • Environmental Engineering 167
  • Computer Vision and Pattern Recognition 132
  • Ecology 113
  • Aerospace Engineering 64
Replace Manuel Vázquez-Arellano with:
Manuel Vázquez-Arellano Germany
Ruifang Zhai China
Juan M. Jurado Spain
Nived Chebrolu Germany
Chunlong Zhang China
Dimitris Zermas United States
Shangpeng Sun China
José M. Bengochea-Guevara Spain
Jingyao Gai United States
Federico Magistri relative to Manuel Vázquez-Arellano Germany Manuel Vázquez-Arellano's profile →
Citations per field
00.5×4.9×
Manuel Vázquez-Arellano · 1×
Citations per year

Countries citing papers authored by Federico Magistri

Since Specialization
Citations

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

Fields of papers citing papers by Federico Magistri

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Federico Magistri

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

All Works

20 of 20 papers shown
#WorkIndexed citations
1 0
2 3
3 22
4 6
5 6
6 2
7 2
8 18
9 19
10 13
11 5
12 7
13 23
14 6
15 34
16 8
17 80
18 32
19 14
20 39

About Federico Magistri

Federico Magistri is a scholar working on Computer Vision and Pattern Recognition, Environmental Engineering and Plant Science, having authored 32 papers that have together received 492 indexed citations. Recurring topics across this work include Smart Agriculture and AI (23 papers), Remote Sensing and LiDAR Applications (9 papers) and Remote Sensing in Agriculture (7 papers). The work is most often cited by research in Environmental Engineering (167 citations), Plant Science (324 citations) and Geology (40 citations). Federico Magistri has collaborated with scholars based in Germany, United Kingdom and Italy. Frequent co-authors include Cyrill Stachniss, Jens Behley, Nived Chebrolu, Thomas Läbe, Marija Popović, Tiziano Guadagnino, Radu Alexandru Roşu, Jens Léon, Heiner Kuhlmann and Stefan Paulus. Their work appears in journals such as PLoS ONE, IEEE Transactions on Pattern Analysis and Machine Intelligence and IEEE Transactions on Robotics.

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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