Francesco Isgrò

2.3k citations
66 papers · 903 indexed · 1 hit paper · h-index 14

Francesco Isgrò

57 papers receiving 861 citations

Hit Papers

A survey on modern trainable activation functions3222021202620222024100200300

Peers

Francesco Isgrò
Comparison fields: 5 of 136
  • Computer Vision and Pattern Recognition 357
  • Artificial Intelligence 239
  • Media Technology 63
  • Signal Processing 71
  • Computer Graphics and Computer-Aided Design 19
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Hong Zhou China
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Citations per year

Countries citing papers authored by Francesco Isgrò

Since Specialization
Citations

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

Fields of papers citing papers by Francesco Isgrò

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network

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

All Works

20 of 20 papers shown
#Work
1 20250
2 20250
3 20250
4 20250
5 20253
6 20242
7 202317
8 20232
9 202335
10 202318
11 20228
12 202224
13 202211
14 202220
15
A survey on modern trainable activation functionsbreakdown →
2021322
16
Explaining classification systems using sparse dictionaries.
20192
17 201813
18 201632
19
Clustering for Surface Reconstruction
20051
20
3-D image processing in the future of immersive media
20041

About Francesco Isgrò

Francesco Isgrò is a scholar working on Computer Vision and Pattern Recognition, Computer Graphics and Computer-Aided Design and Artificial Intelligence, having authored 66 papers that have together received 903 indexed citations. Recurring topics across this work include Advanced Vision and Imaging (15 papers), Advanced Image and Video Retrieval Techniques (9 papers), Robotics and Sensor-Based Localization (6 papers), Solar Radiation and Photovoltaics (5 papers), Atmospheric aerosols and clouds (5 papers), Optical measurement and interference techniques (5 papers), Image and Object Detection Techniques (4 papers) and Image Retrieval and Classification Techniques (4 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (357 citations), Artificial Intelligence (239 citations) and Media Technology (63 citations). Francesco Isgrò has collaborated with scholars based in Italy, United Kingdom and Germany. Frequent co-authors include Andrea Apicella, Roberto Prevete, Francesco Donnarumma, Emanuele Trucco, Domenico Tegolo, Francesca Odone, Alessandro Verri, Oliver Schreer, Peter Kauff and M. Pilu. Their work appears in journals such as SHILAP Revista de lepidopterología, IEEE Transactions on Geoscience and Remote Sensing and IEEE Access.

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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