En‐hui Yang

157 papers receiving 2.2k citations

Peers

En‐hui Yang
Comparison fields: 5 of 98
  • Signal Processing 561
  • Computer Vision and Pattern Recognition 888
  • Computational Theory and Mathematics 538
  • Artificial Intelligence 999
  • Computer Networks and Communications 651
Replace Glen G. Langdon with:
Glen G. Langdon United States
Dongdai Lin China
Xuejia Lai China
In‐Cheol Park South Korea
Johannes Blömer Germany
Kai Lü China
Roger Woods United Kingdom
Bassem Abd-El-Atty Egypt
S. Rao Kosaraju United States
Mohammad Reza Aref Iran
En‐hui Yang relative to Glen G. Langdon United States Glen G. Langdon's profile →
Citations per field
00.5×2×3.4×
Glen G. Langdon · 1×
Citations per year

Countries citing papers authored by En‐hui Yang

Since Specialization
Citations

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

Fields of papers citing papers by En‐hui Yang

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by En‐hui Yang. 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 En‐hui Yang. The network helps show where En‐hui Yang may publish in the future.

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 168 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2000243
2 2009111
3 199881
4 199776
5 200776
6 200075
7 200067
8 200063
9 202062
10 200358
11 199656
12 199751
13 201545
14 200939
15 199939
16 200935
17 200833
18 201732
19 201430
20 201428

About En‐hui Yang

En‐hui Yang is a scholar working on Computer Vision and Pattern Recognition, Signal Processing, Artificial Intelligence, Computational Theory and Mathematics and Computer Networks and Communications, having authored 168 papers that have together received 2.2k indexed citations. Recurring topics across this work include Algorithms and Data Compression (54 papers), Advanced Data Compression Techniques (49 papers), Video Coding and Compression Technologies (36 papers), DNA and Biological Computing (36 papers), Wireless Communication Security Techniques (34 papers), Error Correcting Code Techniques (34 papers), Cellular Automata and Applications (32 papers) and Advanced Vision and Imaging (20 papers). The work is most often cited by research in Signal Processing (561 citations), Computer Vision and Pattern Recognition (888 citations), Computational Theory and Mathematics (538 citations), Artificial Intelligence (999 citations) and Computer Networks and Communications (651 citations). En‐hui Yang has collaborated with scholars based in Canada, United States and China. Frequent co-authors include John C. Kieffer, Dake He, Nan Hu, Jin Meng, Xiang Yang Yu, Haiquan Wang, Zhijin Zhao, Wei Zhang, Chang Sun and Victor K. Wei. Their work appears in journals such as IEEE Transactions on Information Theory, IEEE Transactions on Image Processing, IEEE Transactions on Circuits and Systems for Video Technology, IEEE Transactions on Communications and IEEE Transactions on Wireless Communications.

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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