Xiao-Guang Lv

994 citations
52 papers · 769 indexed · h-index 17
Topics
Image and Signal Denoising Methods (34 papers)Sparse and Compressive Sensing Techniques (25 papers)Advanced Image Processing Techniques (19 papers)
Journals
SHILAP Revista de lepidopterologíaPLoS ONEInformation Sciences

In The Last Decade

Xiao-Guang Lv

51 papers receiving 743 citations

Peers

Xiao-Guang Lv
Comparison fields: 5 of 66
  • Computer Vision and Pattern Recognition 522
  • Computational Mechanics 314
  • Media Technology 190
  • Biomedical Engineering 130
  • Computational Theory and Mathematics 73
Replace Abdelilah Hakim with:
Abdelilah Hakim Morocco
Vincent Duval France
Wolfgang Ring Austria
Tanja Teuber Germany
Tuomo Valkonen Finland
Triet Le United States
Jungho Yoon South Korea
Joachim Stöckler Germany
Rüyam Acar Türkiye
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Xiao-Guang Lv relative to Abdelilah Hakim Morocco Abdelilah Hakim's profile →
Citations per field
00.5×10.5×
Abdelilah Hakim · 1×
Citations per year

Countries citing papers authored by Xiao-Guang Lv

Since Specialization
Citations

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

Fields of papers citing papers by Xiao-Guang Lv

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Xiao-Guang Lv. 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 Xiao-Guang Lv. The network helps show where Xiao-Guang Lv may publish in the future.

Co-authorship network of co-authors of Xiao-Guang Lv

This figure shows the co-authorship network connecting the top 25 collaborators of Xiao-Guang Lv. A scholar is included among the top collaborators of Xiao-Guang Lv 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 Xiao-Guang Lv. Xiao-Guang Lv 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 1
2 3
3 3
4 7
5 6
6 22
7 23
8 17
9 25
10 6
11 3
12 7
13 70
14 15
15 14
16 15
17 8
18 16
19 4
20 6

About Xiao-Guang Lv

Xiao-Guang Lv is a scholar working on Computer Vision and Pattern Recognition, Mathematical Physics and Computational Mechanics, having authored 52 papers that have together received 769 indexed citations. Recurring topics across this work include Image and Signal Denoising Methods (34 papers), Sparse and Compressive Sensing Techniques (25 papers) and Advanced Image Processing Techniques (19 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (522 citations), Media Technology (190 citations) and Computational Mathematics (11 citations). Xiao-Guang Lv has collaborated with scholars based in China, United States and Hong Kong. Frequent co-authors include Ting‐Zhu Huang, Jun Liu, Le Jiang, Fang Li, Po‐Yu Chen, Ivan Selesnick, Zongben Xu, Jun Liu, Xi-Le Zhao and Si Wang. Their work appears in journals such as SHILAP Revista de lepidopterología, PLoS ONE and Information Sciences.

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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