Cong Jin

1.3k citations
81 papers · 983 · h-index 20

Impact in

Papers in

Cong Jin

74 papers receiving 911 citations

Peers

Cong Jin
Comparison fields: 5 of 95
  • Software 276
  • Computer Science Applications 80
  • Information Systems 311
  • Computer Vision and Pattern Recognition 279
  • Computer Networks and Communications 229
Replace Qing Gu with:
Qing Gu China
Sultan Aljahdali Saudi Arabia
Marta Cimitile Italy
Zhiqiang Li China
Yifeng Zhang China
Pravin Chandra India
Shaojin Geng China
Daniel Clancy United States
Harpreet Singh United States
Cong Jin relative to Qing Gu China Qing Gu's profile →
Citations per field
00.5×4.7×
Qing Gu · 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 81 papers — load more, or switch the sort, to bring in the rest.

#Work
1 201576
2 202056
3 201256
4 201352
5 202152
6 201551
7 201547
8 200839
9 201436
10 201034
11 201734
12
A Color Image Encryption Scheme Based on Arnold Scrambling and Quantum Chaotic.
201732
13 200827
14 200827
15 201225
16 202123
17 201123
18 201521
19 202020
20 200719

About Cong Jin

Cong Jin is a scholar working on Computer Vision and Pattern Recognition, Computer Networks and Communications, Information Systems, Software and Artificial Intelligence, having authored 81 papers that have together received 983 indexed citations. Recurring topics across this work include Advanced Steganography and Watermarking Techniques (25 papers), Software Engineering Research (15 papers), Software Reliability and Analysis Research (15 papers), Chaos-based Image/Signal Encryption (15 papers), Digital Media Forensic Detection (13 papers), Image Retrieval and Classification Techniques (11 papers), Advanced Image and Video Retrieval Techniques (9 papers) and Software System Performance and Reliability (9 papers). The work is most often cited by research in Software (276 citations), Computer Science Applications (80 citations), Information Systems (311 citations), Computer Vision and Pattern Recognition (279 citations) and Computer Networks and Communications (229 citations). Cong Jin has collaborated with scholars based in China, France and Burundi. Frequent co-authors include Shu‐Wei Jin, S.W. Jin, Hui Liu, Jinan Liu, Wei Zhang, Jinghua Wang, Jinghua Wang, Shuicai Wu, Baiwen Zhang and Guangyu Bin. Their work appears in journals such as Applied Soft Computing, Multimedia Tools and Applications, Soft Computing, Journal of Visual Communication and Image Representation and Journal of Intelligent & Fuzzy Systems.

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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