Valerio Biscione

555 citations
13 papers · 222 indexed · h-index 7
Topics
Face Recognition and Perception (5 papers)Visual perception and processing mechanisms (4 papers)Domain Adaptation and Few-Shot Learning (3 papers)

In The Last Decade

Valerio Biscione

13 papers receiving 209 citations

Peers

Valerio Biscione
Comparison fields: 5 of 61
  • Cognitive Neuroscience 103
  • Information Systems 58
  • Computer Vision and Pattern Recognition 57
  • Signal Processing 51
  • Artificial Intelligence 35
Replace Md Shafaeat Hossain with:
Md Shafaeat Hossain United States
Gibrán Fuentes-Pineda Mexico
Matthew Yee-King United Kingdom
Akhil Raju India
Kalaivani Sundararajan United States
Stanislav Ondáš Slovakia
Tamara Bonaci United States
Tristan Jehan United States
Efe Bozkir Germany
Hidetake Uwano Japan
Valerio Biscione relative to Md Shafaeat Hossain United States Md Shafaeat Hossain's profile →
Citations per field
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Md Shafaeat Hossain · 1×
Citations per year

Countries citing papers authored by Valerio Biscione

Since Specialization
Citations

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

Fields of papers citing papers by Valerio Biscione

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Valerio Biscione

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

All Works

13 of 13 papers shown
#WorkIndexed citations
1 6
2 1
3 1
4 4
5 68
6 8
7 4
8 8
9 25
10 19
11 1
12 71
13 6

About Valerio Biscione

Valerio Biscione is a scholar working on Cognitive Neuroscience, Human-Computer Interaction and Geology, having authored 13 papers that have together received 222 indexed citations. Recurring topics across this work include Face Recognition and Perception (5 papers), Visual perception and processing mechanisms (4 papers) and Domain Adaptation and Few-Shot Learning (3 papers). The work is most often cited by research in Human-Computer Interaction (31 citations), Cognitive Neuroscience (103 citations) and Signal Processing (51 citations). Valerio Biscione has collaborated with scholars based in United Kingdom, Germany and United States. Frequent co-authors include Hataichanok Saevanee, Nathan Clarke, Steven Furnell, Jeffrey S. Bowers, Orestis Georgiou, Ryan Blything, Marin Dujmović, Federico Adolfi, Gaurav Malhotra and Benjamin D. Evans. Their work appears in journals such as Behavioral and Brain Sciences, Neural Networks and Journal of Machine Learning Research.

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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