Jong‐Wha Chong

1.1k citations
111 papers · 757 · h-index 15

Impact in

Papers in

Jong‐Wha Chong

99 papers receiving 688 citations

Peers

Jong‐Wha Chong
Comparison fields: 5 of 71
  • Signal Processing 197
  • Computer Vision and Pattern Recognition 150
  • Computer Networks and Communications 167
  • Electrical and Electronic Engineering 383
  • Aerospace Engineering 137
Replace Gabriele Meoni with:
Gabriele Meoni Italy
José Vieira Portugal
Akihito Noda Japan
Chao Huang China
Azarakhsh Jalalvand Belgium
Esam Abdel‐Raheem Canada
Mohammad Saquib United States
Raghuraman Mudumbai United States
Oscar Ibarra‐Manzano Mexico
Jong‐Wha Chong relative to Gabriele Meoni Italy Gabriele Meoni's profile →
Citations per field
00.5×10×15×20×22.5×
Gabriele Meoni · 1×
Citations per year

Countries citing papers authored by Jong‐Wha Chong

Since Specialization
Citations

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

Fields of papers citing papers by Jong‐Wha Chong

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Jong‐Wha Chong. 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 Jong‐Wha Chong. The network helps show where Jong‐Wha Chong may publish in the future.

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 111 papers — load more, or switch the sort, to bring in the rest.

#Work
1 201856
2 200350
3 200043
4 201041
5 201937
6 201334
7 201433
8 201527
9 201526
10 201424
11 201220
12 200917
13 200715
14 201015
15 202414
16 201814
17 201012
18 200511
19 201510
20 20069

About Jong‐Wha Chong

Jong‐Wha Chong is a scholar working on Electrical and Electronic Engineering, Computer Vision and Pattern Recognition, Computer Networks and Communications, Signal Processing and Media Technology, having authored 111 papers that have together received 757 indexed citations. Recurring topics across this work include Indoor and Outdoor Localization Technologies (22 papers), Advanced Wireless Communication Techniques (22 papers), Wireless Communication Networks Research (16 papers), Video Coding and Compression Technologies (11 papers), 3D IC and TSV technologies (10 papers), Advanced Vision and Imaging (10 papers), Speech and Audio Processing (10 papers) and Image Processing Techniques and Applications (9 papers). The work is most often cited by research in Signal Processing (197 citations), Computer Vision and Pattern Recognition (150 citations), Computer Networks and Communications (167 citations), Electrical and Electronic Engineering (383 citations) and Aerospace Engineering (137 citations). Jong‐Wha Chong has collaborated with scholars based in South Korea, China and United States. Frequent co-authors include Daegun Oh, Jun Wang, Junkyung Kim, Tae‐Joon Kim, Ki‐Young Jung, Jaehwan Kim, Linbo Luo, Yingchun Li, Sang Eun Kim and Jongho Kim. Their work appears in journals such as ETRI Journal, IEEE Communications Letters, IEEE Transactions on Consumer Electronics, IEEE Transactions on Wireless Communications and Scientific Reports.

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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