Hong Xia

700 citations
55 papers · 473 indexed · h-index 11
Topics
Model Reduction and Neural Networks (8 papers)Service-Oriented Architecture and Web Services (8 papers)Neural Networks and Applications (8 papers)

In The Last Decade

Hong Xia

47 papers receiving 458 citations

Peers

Hong Xia
Comparison fields: 5 of 84
  • Artificial Intelligence 175
  • Control and Systems Engineering 109
  • Computational Mechanics 103
  • Mechanics of Materials 58
  • Information Systems 50
Replace Choi-Hong Lai with:
Choi-Hong Lai United Kingdom
Zeyin Zhang China
Othman M. K. Alsmadi Jordan
Hongrun Wu China
Muhammad Asif Jan Pakistan
Xin Zuo China
Wei Cao China
Neha Yadav India
Liangping Tu China
Riadh Ksantini Canada
Hong Xia relative to Choi-Hong Lai United Kingdom Choi-Hong Lai's profile →
Citations per field
00.5×3.6×
Choi-Hong Lai · 1×
Citations per year

Countries citing papers authored by Hong Xia

Since Specialization
Citations

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

Fields of papers citing papers by Hong Xia

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Hong Xia

This figure shows the co-authorship network connecting the top 25 collaborators of Hong Xia. A scholar is included among the top collaborators of Hong Xia 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 Hong Xia. Hong Xia 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 0
2 0
3 9
4 0
5 9
6 0
7 1
8 29
9 55
10 5
11 10
12
SIFT Image Matching Algorithm Based on Two-dimensional Maximum Entropy-aided Threshold Segmentation
0
13 53
14 2
15 4
16 9
17 1
18 27
19
Development of Space Reflective Thermal Insulation Coatings
1
20 20

About Hong Xia

Hong Xia is a scholar working on Computational Mathematics, Statistical and Nonlinear Physics and Artificial Intelligence, having authored 55 papers that have together received 473 indexed citations. Recurring topics across this work include Model Reduction and Neural Networks (8 papers), Service-Oriented Architecture and Web Services (8 papers) and Neural Networks and Applications (8 papers). The work is most often cited by research in Computational Mathematics (5 citations), Numerical Analysis (30 citations) and Artificial Intelligence (175 citations). Hong Xia has collaborated with scholars based in China, United Kingdom and United States. Frequent co-authors include C.J. Harris, Zhendong Luo, Sheng Chen, Hao Chen, Yu Gong, S.A. Billings, Pradip Majumdar, Yanping Chen, Haoran Wang and Eric R. Weeks. Their work appears in journals such as Sensors, IEEE Transactions on Fuzzy Systems and IEEE Transactions on Cybernetics.

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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