G. Valli

39 papers receiving 859 citations

Peers

G. Valli
Comparison fields: 5 of 105
  • Radiology, Nuclear Medicine and Imaging 352
  • Computer Vision and Pattern Recognition 331
  • Artificial Intelligence 244
  • Cardiology and Cardiovascular Medicine 231
  • Biomedical Engineering 204
Replace Tomasz Markiewicz with:
Tomasz Markiewicz Poland
Giuseppe Coppini Italy
V. S. Chouhan India
M. Muthu Rama Krishnan India
Chenchu Xu China
Shivajirao M. Jadhav India
John Stoitsis Greece
Benqiang Yang China
Barjinder Singh Saini India
Kersten Petersen Denmark
G. Valli relative to Tomasz Markiewicz Poland Tomasz Markiewicz's profile →
Citations per field
00.5×1.5×
Tomasz Markiewicz · 1×
Citations per year

Countries citing papers authored by G. Valli

Since Specialization
Citations

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

Fields of papers citing papers by G. Valli

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of G. Valli

This figure shows the co-authorship network connecting the top 25 collaborators of G. Valli. A scholar is included among the top collaborators of G. Valli 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 G. Valli. G. Valli 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 98
2
Il PM10 a Milano: risultati di una campagna di misura invernale
1
3 76
4 2
5 7
6 9
7
Neural networks and prior knowledge help the segmentation of medical images
4
8 2
9 87
10
Neural Networks Architecture Optimization: A Survey
1
11 23
12 181
13 76
14 14
15 2
16 20
17
Energy-dependent imaging in digital radiography: a review on acquisition, processing and display techniques.
1
18 4
19
AUTOMATED ANALYSIS OF MYOCARDIAL AUTORADIOGRAPHS FOR THE STUDY OF REGIONAL GLUCOSE METABOLISM.
1
20 5

About G. Valli

G. Valli is a scholar working on Computer Vision and Pattern Recognition, Radiology, Nuclear Medicine and Imaging and Artificial Intelligence, having authored 41 papers that have together received 928 indexed citations. Recurring topics across this work include Medical Image Segmentation Techniques (16 papers), Neural Networks and Applications (8 papers) and Image and Signal Denoising Methods (7 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (331 citations), Radiology, Nuclear Medicine and Imaging (352 citations) and Cardiology and Cardiovascular Medicine (231 citations). G. Valli has collaborated with scholars based in Italy, United Kingdom and Czechia. Frequent co-authors include Riccardo Poli, Giuseppe Coppini, Stefano Cagnoni, Stefano Diciotti, Massimo Falchini, Natale Villari, Leonardo Bocchi, Jacopo Nori, R. Livi and Giulia Picozzi. Their work appears in journals such as IEEE Transactions on Pattern Analysis and Machine Intelligence, IEEE Transactions on Biomedical Engineering and IEEE Transactions on Medical Imaging.

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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