Jun Xin

2.6k citations
127 papers · 2.1k · h-index 24

Impact in

Papers in

Jun Xin

122 papers receiving 2.0k citations

Peers

Jun Xin
Comparison fields: 5 of 118
  • Signal Processing 637
  • Computer Vision and Pattern Recognition 689
  • Obstetrics and Gynecology 107
  • Fluid Flow and Transfer Processes 61
  • Radiology, Nuclear Medicine and Imaging 191
Replace Kun Song with:
Kun Song China
Tomoyuki Miyashita Japan
Shin-ichiro Umemura Japan
Soo‐Yong Lee South Korea
Ali Khamene United States
Tong Ding China
Weiming Liu China
Paul Swain United Kingdom
Yichi Zhang China
Sachin Jambawalikar United States
Jun Xin relative to Kun Song China Kun Song's profile →
Citations per field
00.5×10×15×20×24.5×
Kun Song · 1×
Citations per year

Countries citing papers authored by Jun Xin

Since Specialization
Citations

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

Fields of papers citing papers by Jun Xin

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 127 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2004231
2 2009168
3
View Synthesis for Multiview Video Compression
200679
4 200872
5
Coding Approaches for End-To-End 3D TV Systems
200460
6 200652
7 201744
8 201843
9 200842
10 200942
11 200541
12 202040
13 200437
14 200736
15 200536
16 201935
17 199935
18 200734
19 201431
20 200829

About Jun Xin

Jun Xin is a scholar working on Computer Vision and Pattern Recognition, Signal Processing, Materials Chemistry, Electrical and Electronic Engineering and Biomedical Engineering, having authored 127 papers that have together received 2.1k indexed citations. Recurring topics across this work include Video Coding and Compression Technologies (23 papers), Advanced Vision and Imaging (14 papers), Acoustic Wave Resonator Technologies (12 papers), Silicon Carbide Semiconductor Technologies (12 papers), Advanced Data Compression Techniques (12 papers), Image and Video Quality Assessment (10 papers), Endometrial and Cervical Cancer Treatments (10 papers) and Ferroelectric and Piezoelectric Materials (9 papers). The work is most often cited by research in Signal Processing (637 citations), Computer Vision and Pattern Recognition (689 citations), Obstetrics and Gynecology (107 citations), Fluid Flow and Transfer Processes (61 citations) and Radiology, Nuclear Medicine and Imaging (191 citations). Jun Xin has collaborated with scholars based in China, United States and Japan. Frequent co-authors include Ming–Ting Sun, Anthony Vetro, Chia‐Wen Lin, Yanqing Zheng, Haikuan Kong, Huifang Sun, Er‐Wei Shi, Hongzan Sun, Shujun Zhang and Thomas R. Shrout. Their work appears in journals such as Medicine, Nuclear Medicine Communications, European Journal of Radiology, SAE technical papers on CD-ROM/SAE technical paper series and Journal of Crystal Growth.

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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