Paolo Andreini

537 citations
22 papers · 246 · h-index 10

Impact in

  • Biophysics top 10%
    • Cell Image Analysis Techniques
    • Medical Image Segmentation Techniques
    • Advanced Neural Network Applications
    • Handwritten Text Recognition Techniques
    • Generative Adversarial Networks and Image Synthesis

Papers in

Paolo Andreini

21 papers receiving 245 citations

Peers

Paolo Andreini
Comparison fields: 5 of 68
  • Biophysics 38
  • Computer Vision and Pattern Recognition 116
  • Media Technology 26
  • Artificial Intelligence 76
  • Health Informatics 3
Replace Huadeng Wang with:
Huadeng Wang China
Jiří Borovec Czechia
Ashkan Tashk Iran
Aimon Rahman Bangladesh
Nadia Brancati Italy
Somsak Choomchuay Thailand
Santanu Roy India
Thomas Wollmann Germany
Mo Zhang United States
Priyadarshini Adyasha Pattanaik India
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Citations per field
00.5×3.7×
Huadeng Wang · 1×
Citations per year

Countries citing papers authored by Paolo Andreini

Since Specialization
Citations

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

Fields of papers citing papers by Paolo Andreini

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 22 papers — load more, or switch the sort, to bring in the rest.

#Work
1 201954
2 202144
3 202040
4 201615
5 202115
6
Graph Neural Networks for the Prediction of Protein-Protein Interfaces.
202013
7 202212
8 201911
9 20219
10 20239
11 20226
12 20223
13 20203
14 20223
15 20242
16 20192
17 20241
18
Nowcasting German GDP
20201
19 20251
20 20161

About Paolo Andreini

Paolo Andreini is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence, Molecular Biology, Biophysics and General Economics, Econometrics and Finance, having authored 22 papers that have together received 246 indexed citations. Recurring topics across this work include Medical Image Segmentation Techniques (5 papers), Cell Image Analysis Techniques (3 papers), AI in cancer detection (3 papers), Advanced Neural Network Applications (3 papers), Image Processing and 3D Reconstruction (2 papers), Italy: Economic History and Contemporary Issues (2 papers), Gut microbiota and health (2 papers) and Domain Adaptation and Few-Shot Learning (2 papers). The work is most often cited by research in Biophysics (38 citations), Computer Vision and Pattern Recognition (116 citations), Media Technology (26 citations), Artificial Intelligence (76 citations) and Health Informatics (3 citations). Paolo Andreini has collaborated with scholars based in Italy, Germany and United Kingdom. Frequent co-authors include Simone Bonechi, Monica Bianchini, Franco Scarselli, A. Mecocci, Giovanna Maria Dimitri, Caterina Graziani, Andrea Sodi, A. Mecocci, Alberto Rossi and Andrea Garzelli. Their work appears in journals such as Electronics, Neurocomputing, International Journal of Forecasting, Computer Methods and Programs in Biomedicine and Computer Standards & Interfaces.

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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