Giuseppe Coppini

1.3k citations
51 papers · 906 · h-index 17

Impact in

Papers in

Giuseppe Coppini

50 papers receiving 849 citations

Peers

Giuseppe Coppini
Comparison fields: 5 of 114
  • Radiology, Nuclear Medicine and Imaging 295
  • Computer Vision and Pattern Recognition 288
  • Cardiology and Cardiovascular Medicine 180
  • Artificial Intelligence 216
  • Health Information Management 28
Replace Marı́a J. Lado with:
Marı́a J. Lado Spain
G. Valli Italy
Bülent Yılmaz Türkiye
Burak Acar Türkiye
Tomasz Markiewicz Poland
Kamil Říha Czechia
Marcos Martín‐Fernández Spain
Manuel G. Penedo Spain
John Stoitsis Greece
Giuseppe Coppini relative to Marı́a J. Lado Spain Marı́a J. Lado's profile →
Citations per field
00.5×2.8×
Marı́a J. Lado · 1×
Citations per year

Countries citing papers authored by Giuseppe Coppini

Since Specialization
Citations

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

Fields of papers citing papers by Giuseppe Coppini

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 51 papers — load more, or switch the sort, to bring in the rest.

#Work
1 199199
2 199185
3 200482
4 200376
5 199576
6 201844
7 201232
8 201031
9 201531
10 200625
11 199524
12 200924
13 199321
14 199721
15 199120
16 199320
17 199418
18 199015
19 199214
20 199912

About Giuseppe Coppini

Giuseppe Coppini is a scholar working on Computer Vision and Pattern Recognition, Radiology, Nuclear Medicine and Imaging, Cardiology and Cardiovascular Medicine, Artificial Intelligence and Pulmonary and Respiratory Medicine, having authored 51 papers that have together received 906 indexed citations. Recurring topics across this work include Medical Image Segmentation Techniques (14 papers), Neural Networks and Applications (6 papers), Cardiovascular Health and Disease Prevention (5 papers), Radiomics and Machine Learning in Medical Imaging (5 papers), Image and Signal Denoising Methods (5 papers), AI in cancer detection (4 papers), Medical Imaging Techniques and Applications (4 papers) and Cardiovascular Disease and Adiposity (4 papers). The work is most often cited by research in Radiology, Nuclear Medicine and Imaging (295 citations), Computer Vision and Pattern Recognition (288 citations), Cardiology and Cardiovascular Medicine (180 citations), Artificial Intelligence (216 citations) and Health Information Management (28 citations). Giuseppe Coppini has collaborated with scholars based in Italy, Sweden and United Kingdom. Frequent co-authors include G. Valli, Riccardo Poli, A. Colantuoni, S. Bertuglia, Leonardo Bocchi, Marcos Intaglietta, Stefano Cagnoni, Stefano Diciotti, Jacopo Nori and Massimo Falchini. Their work appears in journals such as IEEE Transactions on Medical Imaging, Computer, Pattern Recognition Letters, IEEE Transactions on Pattern Analysis and Machine Intelligence and Applied Sciences.

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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