Cheng-Hsing Yang

1.2k citations
42 papers · 906 · h-index 13

Impact in

Papers in

Cheng-Hsing Yang

42 papers receiving 820 citations

Peers

Cheng-Hsing Yang
Comparison fields: 5 of 30
  • Computer Vision and Pattern Recognition 866
  • Signal Processing 44
  • Media Technology 27
  • Computational Theory and Mathematics 36
  • Artificial Intelligence 63
Replace Andrew D. Ker with:
Andrew D. Ker United Kingdom
Chi-Yao Weng Taiwan
Kedar Nath Singh India
Dalel Bouslimi France
Xiangli Xiao China
David Soukal United States
F. Deguillaume Switzerland
Da-Chun Wu Taiwan
Ling Du China
Luis Pérez-Freire Spain
Cheng-Hsing Yang relative to Andrew D. Ker United Kingdom Andrew D. Ker's profile →
Citations per field
00.5×1.5×
Andrew D. Ker · 1×
Citations per year

Countries citing papers authored by Cheng-Hsing Yang

Since Specialization
Citations

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

Fields of papers citing papers by Cheng-Hsing Yang

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Cheng-Hsing 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 Cheng-Hsing Yang. The network helps show where Cheng-Hsing Yang may publish in the future.

Co-authors

The 20 scholars most cited alongside Cheng-Hsing 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 Cheng-Hsing Yang Line = papers co-authored together Cheng-Hsing Yang links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 42 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2008314
2 2008106
3 201061
4 200960
5 201057
6 201137
7 201036
8 201134
9 202219
10 200617
11 201017
12 202214
13 201312
14 200712
15 201011
16 201111
17 202310
18 200410
19 199310
20 20148

About Cheng-Hsing Yang

Cheng-Hsing Yang is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence, Signal Processing, Computational Theory and Mathematics and Electrical and Electronic Engineering, having authored 42 papers that have together received 906 indexed citations. Recurring topics across this work include Advanced Steganography and Watermarking Techniques (33 papers), Chaos-based Image/Signal Encryption (30 papers), Digital Media Forensic Detection (24 papers), Advanced Data Compression Techniques (5 papers), Cryptography and Data Security (4 papers), Video Coding and Compression Technologies (3 papers), Advanced Graph Theory Research (3 papers) and Algorithms and Data Compression (3 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (866 citations), Signal Processing (44 citations), Media Technology (27 citations), Computational Theory and Mathematics (36 citations) and Artificial Intelligence (63 citations). Cheng-Hsing Yang has collaborated with scholars based in Taiwan and United States. Frequent co-authors include Shiuh-Jeng Wang, Chi-Yao Weng, Hung–Min Sun, Hao-Kuan Tso, Cheng-Ta Huang, Wei-Jen Wang, Chin‐Feng Lee, Chi-Yao Weng, Jianyu Chen and Fu‐Hau Hsu. Their work appears in journals such as Journal of Visual Communication and Image Representation, Journal of Systems and Software, Multimedia Tools and Applications, ACM Transactions on Design Automation of Electronic Systems and Computer Standards & Interfaces.

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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