Deyun Wei

1.6k citations
60 papers · 1.3k · h-index 21

Impact in

Papers in

Deyun Wei

57 papers receiving 1.3k citations

Peers

Deyun Wei
Comparison fields: 5 of 61
  • Applied Mathematics 790
  • Computer Vision and Pattern Recognition 1.0k
  • Signal Processing 533
  • Control and Systems Engineering 151
  • Media Technology 49
Replace Çağatay Candan with:
Çağatay Candan Türkiye
Bing‐Zhao Li China
Min-Hung Yeh Taiwan
Eckhard Hitzer Japan
Naitong Zhang China
Ahmed I. Zayed United States
Amina Chebira United States
Eric Weber United States
Masaru Takeuchi Japan
Deyun Wei relative to Çağatay Candan Türkiye Çağatay Candan's profile →
Citations per field
00.5×
Çağatay Candan · 1×
Citations per year

Countries citing papers authored by Deyun Wei

Since Specialization
Citations

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

Fields of papers citing papers by Deyun Wei

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 18 scholars most cited alongside Deyun Wei, 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 Deyun Wei Line = papers co-authored together Deyun Wei links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 60 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2009118
2 202281
3 201975
4 201169
5 202169
6 201455
7 201447
8 201946
9 201142
10 201541
11 202139
12 201138
13 202234
14 201634
15 201632
16 201129
17 201126
18 201526
19 202122
20 202321

About Deyun Wei

Deyun Wei is a scholar working on Computer Vision and Pattern Recognition, Applied Mathematics, Signal Processing, Control and Systems Engineering and Artificial Intelligence, having authored 60 papers that have together received 1.3k indexed citations. Recurring topics across this work include Image and Signal Denoising Methods (41 papers), Mathematical Analysis and Transform Methods (39 papers), Digital Filter Design and Implementation (27 papers), Chaos-based Image/Signal Encryption (7 papers), Machine Fault Diagnosis Techniques (6 papers), Advanced Graph Neural Networks (6 papers), Advanced Steganography and Watermarking Techniques (5 papers) and Advanced Image Processing Techniques (4 papers). The work is most often cited by research in Applied Mathematics (790 citations), Computer Vision and Pattern Recognition (1.0k citations), Signal Processing (533 citations), Control and Systems Engineering (151 citations) and Media Technology (49 citations). Deyun Wei has collaborated with scholars based in China. Frequent co-authors include Yuanmin Li, Yijie Zhang, Liying Tan, Jing Ma, Huimin Hu, Yi Shen, Wenwen Yang, Yong Li, Xiyang Zhi and Wei Zhang. Their work appears in journals such as Optik, Signal Processing, Digital Signal Processing, IEEE Transactions on Signal Processing and IEEE Signal Processing Letters.

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.

Explore authors with similar magnitude of impact