Cong Jin

1.2k citations
91 papers · 839 · h-index 17

Impact in

Papers in

Cong Jin

78 papers receiving 807 citations

Peers

Cong Jin
Comparison fields: 5 of 124
  • Safety, Risk, Reliability and Quality 202
  • Polymers and Plastics 232
  • Signal Processing 128
  • Computer Vision and Pattern Recognition 223
  • Aerospace Engineering 95
Replace Weiyi Liu with:
Weiyi Liu China
Jie Zhen Hu China
Luiz Henrique Meyer Brazil
Yuxuan Zhang China
Ming Ke Dong China
Wu Wang China
Taikyeong Ted. Jeong South Korea
SHAOFAN WANG China
Cong Jin relative to Weiyi Liu China Weiyi Liu's profile →
Citations per field
00.5×2×3×4×5.0×
Weiyi Liu · 1×
Citations per year

Countries citing papers authored by Cong Jin

Since Specialization
Citations

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

Fields of papers citing papers by Cong Jin

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 91 papers — load more, or switch the sort, to bring in the rest.

#Work
1 201849
2 201346
3 201145
4 202141
5 202239
6 201638
7 201838
8 202036
9 202334
10 202129
11 202327
12 201727
13 201923
14 201921
15 202021
16 202321
17 201418
18 202217
19 200617
20 202014

About Cong Jin

Cong Jin is a scholar working on Computer Vision and Pattern Recognition, Safety, Risk, Reliability and Quality, Signal Processing, Polymers and Plastics and Aerospace Engineering, having authored 91 papers that have together received 839 indexed citations. Recurring topics across this work include Music and Audio Processing (17 papers), Fire dynamics and safety research (17 papers), Flame retardant materials and properties (14 papers), Music Technology and Sound Studies (12 papers), Generative Adversarial Networks and Image Synthesis (7 papers), Video Analysis and Summarization (7 papers), Combustion and Detonation Processes (7 papers) and Speech and Audio Processing (6 papers). The work is most often cited by research in Safety, Risk, Reliability and Quality (202 citations), Polymers and Plastics (232 citations), Signal Processing (128 citations), Computer Vision and Pattern Recognition (223 citations) and Aerospace Engineering (95 citations). Cong Jin has collaborated with scholars based in China, Australia and Slovakia. Frequent co-authors include Qiang Xu, Yong Jiang, Rhoda Afriyie Mensah, Ming Gao Yan, Andrea Majlingová, Solomon Asante‐Okyere, Yun Tie, Lin Jiang, Jiaxiong Peng and Xin Lv. Their work appears in journals such as Journal of Thermal Analysis and Calorimetry, Wireless Communications and Mobile Computing, Journal of Clinical Investigation, Experimental Brain Research and Human Vaccines & Immunotherapeutics.

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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