Chong Fu

2.6k citations
134 papers · 1.8k indexed · h-index 20

Impact in

Papers in

Chong Fu

120 papers receiving 1.7k citations

Peers

Chong Fu
Comparison fields: 5 of 121
  • Computer Vision and Pattern Recognition 1.1k
  • Artificial Intelligence 618
  • Mathematical Physics 165
  • Computational Theory and Mathematics 214
  • Statistical and Nonlinear Physics 124
Replace Rengarajan Amirtharajan with:
Rengarajan Amirtharajan India
Camel Tanougast France
Sajjad Shaukat Jamal Saudi Arabia
Fawad Ahmed Pakistan
Mahdi Yaghoobi Iran
Xiaofu Wu China
Lingfeng Niu China
Mhamed Sayyouri Morocco
Amany Sarhan Egypt
Yuanyuan Liu China
Chong Fu relative to Rengarajan Amirtharajan India Rengarajan Amirtharajan's profile →
Citations per field
00.5×1.5×
Rengarajan Amirtharajan · 1×
Citations per year

Countries citing papers authored by Chong Fu

Since Specialization
Citations

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

Fields of papers citing papers by Chong Fu

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown
#Work
1 20251
2 20250
3 20251
4 20250
5 20251
6 202510
7 20244
8 20247
9 20240
10 202411
11 20244
12 20233
13 202329
14 20233
15 20238
16 20232
17 20234
18 202216
19 202123
20 201848

About Chong Fu

Chong Fu is a scholar working on Computer Vision and Pattern Recognition, Mathematical Physics, Computational Mathematics, Artificial Intelligence and Statistical and Nonlinear Physics, having authored 134 papers that have together received 1.8k indexed citations. Recurring topics across this work include Chaos-based Image/Signal Encryption (44 papers), Advanced Steganography and Watermarking Techniques (32 papers), Mathematical Dynamics and Fractals (22 papers), Advanced Neural Network Applications (21 papers), AI in cancer detection (16 papers), Advanced Image and Video Retrieval Techniques (12 papers), Chaos control and synchronization (11 papers) and Cellular Automata and Applications (10 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (1.1k citations), Artificial Intelligence (618 citations), Mathematical Physics (165 citations), Computational Theory and Mathematics (214 citations) and Statistical and Nonlinear Physics (124 citations). Chong Fu has collaborated with scholars based in China, New Zealand and United States. Frequent co-authors include Junxin Chen, Wei Song, Chiu‐Wing Sham, Zhiliang Zhu, Ming Tie, Lin Cao, Luping Ji, Zhou Ming-tian, Yushu Zhang and Libo Zhang. Their work appears in journals such as Sensors, Computers in Biology and Medicine, IEEE Sensors Journal, Neural Computing and Applications and IEEE Transactions on Consumer Electronics.

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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