Hwangjun Song

1.4k citations
100 papers · 1.1k · h-index 17

Impact in

Papers in

Hwangjun Song

94 papers receiving 1.1k citations

Peers

Hwangjun Song
Comparison fields: 5 of 69
  • Signal Processing 260
  • Computer Networks and Communications 511
  • Computer Vision and Pattern Recognition 353
  • Oral Surgery 56
  • Orthodontics 28
Replace Xiaoxiang Wang with:
Xiaoxiang Wang China
Vincenzo Riccio Italy
Jatinder Singh India
Wenting Li China
Faraz Ahmed United States
Mohammad S. Hasan United Kingdom
Pan Wei China
Zheng Dong China
Jackrit Suthakorn Thailand
Hwangjun Song relative to Xiaoxiang Wang China Xiaoxiang Wang's profile →
Citations per field
00.5×10×14.4×
Xiaoxiang Wang · 1×
Citations per year

Countries citing papers authored by Hwangjun Song

Since Specialization
Citations

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

Fields of papers citing papers by Hwangjun Song

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 100 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2010137
2 2010108
3 200178
4 200856
5 201552
6 201148
7 201243
8 201439
9 201831
10 200431
11 200026
12 199926
13 201122
14 201721
15 201621
16 201920
17 201216
18 202114
19 201713
20 200713

About Hwangjun Song

Hwangjun Song is a scholar working on Computer Networks and Communications, Computer Vision and Pattern Recognition, Electrical and Electronic Engineering, Signal Processing and Sociology and Political Science, having authored 100 papers that have together received 1.1k indexed citations. Recurring topics across this work include Caching and Content Delivery (31 papers), Image and Video Quality Assessment (30 papers), Cooperative Communication and Network Coding (25 papers), Advanced Wireless Network Optimization (22 papers), Video Coding and Compression Technologies (20 papers), Peer-to-Peer Network Technologies (17 papers), Advanced Data Compression Techniques (11 papers) and Advanced MIMO Systems Optimization (11 papers). The work is most often cited by research in Signal Processing (260 citations), Computer Networks and Communications (511 citations), Computer Vision and Pattern Recognition (353 citations), Oral Surgery (56 citations) and Orthodontics (28 citations). Hwangjun Song has collaborated with scholars based in South Korea, United States and Japan. Frequent co-authors include C.‐C. Jay Kuo, Jin‐Woo Park, Je‐Hee Jang, Youn‐Jeong Kim, Takao Hanawa, Youn Jeong Kim, Inkyu Lee, Jongwon Kim, Wan Kim and Yongseok Park. Their work appears in journals such as IEEE Transactions on Mobile Computing, Journal of Visual Communication and Image Representation, IEEE Transactions on Vehicular Technology, IEEE Transactions on Multimedia and IEEE Transactions on Circuits and Systems for Video Technology.

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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