Ju-Yuan Hsiao
- Computer Vision and Pattern Recognition top 2%
- Media Technology top 10%
- Signal Processing
- Artificial Intelligence
- Electrical and Electronic Engineering
- Co-authors
- Chin‐Chen ChangJ. Morris ChangYung‐Kuan ChanChien‐Hung HuangPo‐Yueh ChenShyh‐Jye JouChi‐Shiang Chan
- Topics
- Advanced Steganography and Watermarking Techniques (9 papers)Chaos-based Image/Signal Encryption (8 papers)Digital Media Forensic Detection (7 papers)
- Cited by
- Computer Vision and Pattern RecognitionMedia TechnologyComputer Graphics and Computer-Aided Design
- Partner nations
- TaiwanUnited States
In The Last Decade
Ju-Yuan Hsiao
18 papers receiving 432 citations
Peers
Comparison fields: 5 of 51
- Computer Vision and Pattern Recognition 447
- Media Technology 40
- Signal Processing 29
- Artificial Intelligence 28
- Electrical and Electronic Engineering 20
Countries citing papers authored by Ju-Yuan Hsiao
This map shows the geographic impact of Ju-Yuan Hsiao'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 Ju-Yuan Hsiao with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Ju-Yuan Hsiao more than expected).
Fields of papers citing papers by Ju-Yuan Hsiao
This network shows the impact of papers produced by Ju-Yuan Hsiao. 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 Ju-Yuan Hsiao. The network helps show where Ju-Yuan Hsiao may publish in the future.
Co-authorship network of co-authors of Ju-Yuan Hsiao
This figure shows the co-authorship network connecting the top 25 collaborators of Ju-Yuan Hsiao. A scholar is included among the top collaborators of Ju-Yuan Hsiao 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 Ju-Yuan Hsiao. Ju-Yuan Hsiao is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 2 | |
| 2 | Reversible Data Hiding Based on Pairwise Prediction-Error Histogram. | 4 |
| 3 | 1 | |
| 4 | 7 | |
| 5 | 85 | |
| 6 | 2 | |
| 7 | 64 | |
| 8 | 7 | |
| 9 | 14 | |
| 10 | 4 | |
| 11 | 3 | |
| 12 | 18 | |
| 13 | 3 | |
| 14 | Boceedings of ICCT2003 A New Approach to Lossless Image Compression | 2 |
| 15 | 2 | |
| 16 | 265 | |
| 17 | 4 | |
| 18 | 7 |
About Ju-Yuan Hsiao
Ju-Yuan Hsiao is a scholar working on Computer Vision and Pattern Recognition, Computer Graphics and Computer-Aided Design and Signal Processing, having authored 18 papers that have together received 494 indexed citations. Recurring topics across this work include Advanced Steganography and Watermarking Techniques (9 papers), Chaos-based Image/Signal Encryption (8 papers) and Digital Media Forensic Detection (7 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (447 citations), Media Technology (40 citations) and Computer Graphics and Computer-Aided Design (11 citations). Ju-Yuan Hsiao has collaborated with scholars based in Taiwan and United States. Frequent co-authors include Chin‐Chen Chang, J. Morris Chang, Yung‐Kuan Chan, Chien‐Hung Huang, Po‐Yueh Chen, Shyh‐Jye Jou and Chi‐Shiang Chan. Their work appears in journals such as Pattern Recognition, Signal Processing and Image and Vision Computing.
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.