Ning Gui

981 citations
52 papers · 653 · h-index 12

Impact in

Papers in

Ning Gui

45 papers receiving 614 citations

Peers

Ning Gui
Comparison fields: 5 of 89
  • Computer Vision and Pattern Recognition 220
  • Demography 76
  • Computer Networks and Communications 148
  • Building and Construction 81
  • Artificial Intelligence 199
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Janez Bešter Slovenia
Mário A. R. Dantas Brazil
Bryan Scotney United Kingdom
Min Mun United States
Daniel Díaz-Sánchez Spain
Hon Cheung Australia
Patrick Reignier France
Nicola Bicocchi Italy
Marcus Handte Germany
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Citations per field
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Citations per year

Countries citing papers authored by Ning Gui

Since Specialization
Citations

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

Fields of papers citing papers by Ning Gui

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 52 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2009182
2 201952
3 202149
4 201738
5 201038
6 201831
7 201920
8 201020
9 200913
10 200812
11 202311
12 202411
13 201211
14 202211
15 200810
16 201210
17 20179
18 20089
19 20239
20 20229

About Ning Gui

Ning Gui is a scholar working on Artificial Intelligence, Information Systems, Computer Networks and Communications, Computer Vision and Pattern Recognition and Control and Systems Engineering, having authored 52 papers that have together received 653 indexed citations. Recurring topics across this work include Service-Oriented Architecture and Web Services (9 papers), Context-Aware Activity Recognition Systems (9 papers), Advanced Software Engineering Methodologies (8 papers), Advanced Graph Neural Networks (8 papers), Software System Performance and Reliability (6 papers), IoT and Edge/Fog Computing (4 papers), Technology Use by Older Adults (4 papers) and Neural Networks and Applications (4 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (220 citations), Demography (76 citations), Computer Networks and Communications (148 citations), Building and Construction (81 citations) and Artificial Intelligence (199 citations). Ning Gui has collaborated with scholars based in China, Belgium and Netherlands. Frequent co-authors include Vincenzo De Florio, Chris Blondia, Hong Sun, Geert Deconinck, Zhifeng Qiu, Weihua Gui, Lingxiang Huang, Young Hoon Joo, Junnan Li and Yuqian Guo. Their work appears in journals such as IEEE Transactions on Knowledge and Data Engineering, International Journal of Electrical Power & Energy Systems, Knowledge-Based Systems, Energy and Buildings and IET Control Theory and Applications.

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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