Grazia Lo Sciuto

81 papers receiving 1.0k citations

Peers

Grazia Lo Sciuto
Comparison fields: 5 of 127
  • Computer Networks and Communications 177
  • Statistical and Nonlinear Physics 82
  • Environmental Engineering 94
  • Energy Engineering and Power Technology 18
  • Artificial Intelligence 176
Replace Simon Y. Foo with:
Simon Y. Foo United States
Eiji Mizutani Taiwan
Li Chai China
Peng Li China
S. Sachin Kumar India
Giacomo Capizzi Italy
Shima Rashidi Iraq
Shun Chen China
Greg Van Houdt Belgium
Tiantian Xie United States
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Citations per year

Countries citing papers authored by Grazia Lo Sciuto

Since Specialization
Citations

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

Fields of papers citing papers by Grazia Lo Sciuto

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Grazia Lo Sciuto. 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 Grazia Lo Sciuto. The network helps show where Grazia Lo Sciuto may publish in the future.

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 84 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2012123
2 201875
3 201973
4 201752
5 201848
6 201045
7 201837
8 201536
9 201733
10 201731
11 200831
12
A Novel Neural Networks-Based Texture Image Processing Algorithm for Orange Defects Classification.
201630
13 201728
14 202027
15 201521
16 201818
17 202117
18 201917
19 201417
20 201316

About Grazia Lo Sciuto

Grazia Lo Sciuto is a scholar working on Electrical and Electronic Engineering, Biomedical Engineering, Mechanical Engineering, Computer Vision and Pattern Recognition and Civil and Structural Engineering, having authored 84 papers that have together received 1.1k indexed citations. Recurring topics across this work include Vibration Control and Rheological Fluids (7 papers), Wireless Power Transfer Systems (6 papers), Energy Load and Power Forecasting (6 papers), Innovative Energy Harvesting Technologies (5 papers), Organic Electronics and Photovoltaics (5 papers), Hydraulic and Pneumatic Systems (5 papers), Industrial Vision Systems and Defect Detection (5 papers) and Building Energy and Comfort Optimization (5 papers). The work is most often cited by research in Computer Networks and Communications (177 citations), Statistical and Nonlinear Physics (82 citations), Environmental Engineering (94 citations), Energy Engineering and Power Technology (18 citations) and Artificial Intelligence (176 citations). Grazia Lo Sciuto has collaborated with scholars based in Italy, Poland and Israel. Frequent co-authors include Giacomo Capizzi, Christian Napoli, Marcin Woźniak, Emiliano Tramontana, Francesco Beritelli, Dawid Połap, Bernd Diekkrüger, Mattia Frasca, Luigi Fortuna and Arturo Buscarino. Their work appears in journals such as Sensors, IEEE Access, Chaos An Interdisciplinary Journal of Nonlinear Science, Electronics and Journal of Materials Science Materials in Electronics.

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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