Simone Fiori

2.5k citations
172 papers · 1.8k indexed · h-index 22
Topics
Blind Source Separation Techniques (88 papers)Neural Networks and Applications (82 papers)Control Systems and Identification (30 papers)
Journals
SHILAP Revista de lepidopterologíaPLoS ONEFood Chemistry
Partner nations
ItalyJapanChina

In The Last Decade

Simone Fiori

160 papers receiving 1.6k citations

Peers

Simone Fiori
Comparison fields: 5 of 119
  • Signal Processing 711
  • Artificial Intelligence 676
  • Control and Systems Engineering 331
  • Computer Vision and Pattern Recognition 281
  • Statistical and Nonlinear Physics 227
Replace N. Kalouptsidis with:
N. Kalouptsidis Greece
Ioannis D. Schizas United States
Antonio Napolitano Italy
Brett Ninness Australia
Bruce W. Suter United States
B.G. Mertzios Greece
Zhenya He China
Esa Ollila Finland
Delin Chu Singapore
Simone Fiori relative to N. Kalouptsidis Greece N. Kalouptsidis's profile →
Citations per field
00.5×3.3×
N. Kalouptsidis · 1×
Citations per year

Countries citing papers authored by Simone Fiori

Since Specialization
Citations

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

Fields of papers citing papers by Simone Fiori

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Simone Fiori

This figure shows the co-authorship network connecting the top 25 collaborators of Simone Fiori. A scholar is included among the top collaborators of Simone Fiori 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 Simone Fiori. Simone Fiori 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 1
2 0
3 6
4 6
5 1
6 1
7 4
8 10
9 3
10 14
11 16
12 2
13
Quasi-Geodesic Neural Learning Algorithms Over the Orthogonal Group: A Tutorial
44
14
Quality enhancement of eddy-current-based non-destructive evaluation data through independent component analysis
1
15 29
16 14
17 43
18 35
19 32
20
A Comparison of Three PCA Neural Techniques
2

About Simone Fiori

Simone Fiori is a scholar working on Signal Processing, Artificial Intelligence and Control and Systems Engineering, having authored 172 papers that have together received 1.8k indexed citations. Recurring topics across this work include Blind Source Separation Techniques (88 papers), Neural Networks and Applications (82 papers) and Control Systems and Identification (30 papers). The work is most often cited by research in Signal Processing (711 citations), Artificial Intelligence (676 citations) and Statistical and Nonlinear Physics (227 citations). Simone Fiori has collaborated with scholars based in Italy, Japan and China. Frequent co-authors include Pietro Burrascano, Toshihisa Tanaka, M. Mongiardo, Francesco Piazza, Tetsuya Kaneko, Elena Celledoni, Miguel A. López‐Manchado, J. Biagiotti, J. M. Kenny and Luigi Torre. Their work appears in journals such as SHILAP Revista de lepidopterología, PLoS ONE and Food Chemistry.

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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