Jun Xian

498 citations
46 papers · 330 · h-index 10

Impact in

Papers in

Jun Xian

40 papers receiving 320 citations

Peers

Jun Xian
Comparison fields: 5 of 61
  • Applied Mathematics 216
  • Mathematical Physics 68
  • Acoustics and Ultrasonics 6
  • Computer Vision and Pattern Recognition 127
  • Computational Mechanics 91
Replace Shai Dekel with:
Shai Dekel Israel
Youming Liu China
Joseph D. Lakey United States
Fritz Keinert United States
Xianliang Shi China
Hongbin Guo United States
Luca Calatroni France
Triet Le United States
Pouya D. Tafti Switzerland
Lasse Borup Denmark
Jun Xian relative to Shai Dekel Israel Shai Dekel's profile →
Citations per field
00.5×1.5×1.8×
Shai Dekel · 1×
Citations per year

Countries citing papers authored by Jun Xian

Since Specialization
Citations

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

Fields of papers citing papers by Jun Xian

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 46 papers — load more, or switch the sort, to bring in the rest.

#Work
1 200638
2 200530
3 201827
4 200725
5 201220
6 201317
7 201016
8 202113
9 202212
10 201911
11 20199
12 20199
13 20099
14 20099
15 20228
16 20138
17 20038
18 20077
19 20237
20 20136

About Jun Xian

Jun Xian is a scholar working on Applied Mathematics, Computer Vision and Pattern Recognition, Computational Mechanics, Radiology, Nuclear Medicine and Imaging and Signal Processing, having authored 46 papers that have together received 330 indexed citations. Recurring topics across this work include Mathematical Analysis and Transform Methods (26 papers), Image and Signal Denoising Methods (19 papers), Sparse and Compressive Sensing Techniques (10 papers), Medical Imaging Techniques and Applications (9 papers), Advanced Numerical Analysis Techniques (5 papers), Advanced Harmonic Analysis Research (4 papers), Seismic Imaging and Inversion Techniques (4 papers) and Adaptive Control of Nonlinear Systems (3 papers). The work is most often cited by research in Applied Mathematics (216 citations), Mathematical Physics (68 citations), Acoustics and Ultrasonics (6 citations), Computer Vision and Pattern Recognition (127 citations) and Computational Mechanics (91 citations). Jun Xian has collaborated with scholars based in China, United States and Germany. Frequent co-authors include Qiyu Sun, Li Song, Hartmut Führ, Wei Lin, Yaxu Li, Wenchang Sun, M. Zuhair Nashed, Jinming Wen, Alan Wee‐Chung Liew and Li Song. Their work appears in journals such as Applied and Computational Harmonic Analysis, Numerical Functional Analysis and Optimization, Inverse Problems, IEEE Signal Processing Letters and Signal Processing.

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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