Ching-Yun Chang

22 total papers · 478 total citations
18 papers, 327 citations indexed

About

Ching-Yun Chang is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence and Management Science and Operations Research. According to data from OpenAlex, Ching-Yun Chang has authored 18 papers receiving a total of 327 indexed citations (citations by other indexed papers that have themselves been cited), including 12 papers in Computer Vision and Pattern Recognition, 11 papers in Artificial Intelligence and 3 papers in Management Science and Operations Research. Recurrent topics in Ching-Yun Chang's work include Advanced Steganography and Watermarking Techniques (11 papers), Digital Media Forensic Detection (7 papers) and Chaos-based Image/Signal Encryption (6 papers). Ching-Yun Chang is often cited by papers focused on Advanced Steganography and Watermarking Techniques (11 papers), Digital Media Forensic Detection (7 papers) and Chaos-based Image/Signal Encryption (6 papers). Ching-Yun Chang collaborates with scholars based in United Kingdom, China and Singapore. Ching-Yun Chang's co-authors include Stephen Clark, Zhongqing Wang, Yue Zhang, Zhihui Wang, Chin‐Feng Lee, Zhiyang Teng, Yue Zhang, Bin Ke, Yue Zhang and Chi‐Shiang Chan and has published in prestigious journals such as Journal of Systems and Software, Computational Linguistics and KSII Transactions on Internet and Information Systems.

In The Last Decade

Ching-Yun Chang

18 papers receiving 302 citations

Author Peers

Peers are selected by citation overlap in the author's most active subfields. citations · hero ref

Author Last Decade Papers Cites
Ching-Yun Chang 188 184 36 32 26 18 327
Zhuang Liu 207 1.1× 78 0.4× 77 2.1× 11 0.3× 11 0.4× 15 286
Yujia Liu 151 0.8× 118 0.6× 26 0.7× 22 0.7× 23 0.9× 15 254
Yawen Zeng 104 0.6× 220 1.2× 14 0.4× 28 0.9× 5 0.2× 23 282
Zhi Li 106 0.6× 206 1.1× 23 0.6× 29 0.9× 69 2.7× 19 321
Yueqi Xie 125 0.7× 155 0.8× 22 0.6× 103 3.2× 34 1.3× 14 294
Chew‐Lim Tan 247 1.3× 133 0.7× 15 0.4× 96 3.0× 31 1.2× 20 363
Saptarshi Chakraborty 217 1.2× 100 0.5× 33 0.9× 28 0.9× 54 2.1× 22 356
Jike Chong 156 0.8× 74 0.4× 14 0.4× 33 1.0× 135 5.2× 25 322
Sundararajan Sellamanickam 205 1.1× 126 0.7× 15 0.4× 51 1.6× 21 0.8× 19 294
Shizhe Diao 198 1.1× 74 0.4× 14 0.4× 25 0.8× 16 0.6× 23 265

Countries citing papers authored by Ching-Yun Chang

Since Specialization
Citations

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

Fields of papers citing papers by Ching-Yun Chang

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Ching-Yun Chang. 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 Ching-Yun Chang. The network helps show where Ching-Yun Chang may publish in the future.

Co-authorship network of co-authors of Ching-Yun Chang

This figure shows the co-authorship network connecting the top 25 collaborators of Ching-Yun Chang. A scholar is included among the top collaborators of Ching-Yun Chang based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Ching-Yun Chang. Ching-Yun Chang is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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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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