Jau-Ji Shen
- Computer Vision and Pattern Recognition top 2%
- Information Systems top 2%
- Computer Networks and Communications top 5%
- Artificial Intelligence top 10%
- Signal Processing top 5%
- Co-authors
- Min‐Shiang HwangChih‐Wei LinChun‐Wei YangChin‐Feng LeeChun‐Ta LiM.R.T. ArrudaA. PaganiYen‐Ping Chu
- Topics
- Advanced Steganography and Watermarking Techniques (27 papers)Digital Media Forensic Detection (24 papers)Chaos-based Image/Signal Encryption (22 papers)
In The Last Decade
Jau-Ji Shen
57 papers receiving 760 citations
Peers
Comparison fields: 5 of 67
- Computer Vision and Pattern Recognition 369
- Information Systems 352
- Computer Networks and Communications 307
- Artificial Intelligence 199
- Signal Processing 164
Countries citing papers authored by Jau-Ji Shen
This map shows the geographic impact of Jau-Ji Shen'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 Jau-Ji Shen with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Jau-Ji Shen more than expected).
Fields of papers citing papers by Jau-Ji Shen
This network shows the impact of papers produced by Jau-Ji Shen. 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 Jau-Ji Shen. The network helps show where Jau-Ji Shen may publish in the future.
Co-authorship network of co-authors of Jau-Ji Shen
This figure shows the co-authorship network connecting the top 25 collaborators of Jau-Ji Shen. A scholar is included among the top collaborators of Jau-Ji Shen 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 Jau-Ji Shen. Jau-Ji Shen is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 0 | |
| 2 | 1 | |
| 3 | 1 | |
| 4 | 2 | |
| 5 | A new approach of lossy image compression based on hybrid image resizing techniques. | 4 |
| 6 | A High-performance Computing Method for Photographic Mosaics upon the Hadoop Framework | 1 |
| 7 | 1 | |
| 8 | 6 | |
| 9 | A Survey of Reversible Data Hiding for VQ-Compressed Images. | 6 |
| 10 | An Improved Dual Image-based Reversible Hiding Technique Using LSB Matching. | 13 |
| 11 | 11 | |
| 12 | 10 | |
| 13 | 9 | |
| 14 | 3 | |
| 15 | 2 | |
| 16 | A Petri-Net Based Modeling Approach to Concurrent Software Engineering Tasks * | 3 |
| 17 | Cryptanalysis of a New Efficient MAKEP for Wireless Communications | 4 |
| 18 | A secure LITESET scheme | 0 |
| 19 | 2 | |
| 20 | 11 |
About Jau-Ji Shen
Jau-Ji Shen is a scholar working on Computer Vision and Pattern Recognition, Computer Graphics and Computer-Aided Design and Information Systems, having authored 62 papers that have together received 847 indexed citations. Recurring topics across this work include Advanced Steganography and Watermarking Techniques (27 papers), Digital Media Forensic Detection (24 papers) and Chaos-based Image/Signal Encryption (22 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (369 citations), Information Systems (352 citations) and Signal Processing (164 citations). Jau-Ji Shen has collaborated with scholars based in Taiwan, Portugal and Italy. Frequent co-authors include Min‐Shiang Hwang, Chih‐Wei Lin, Chun‐Wei Yang, Chin‐Feng Lee, Chun‐Ta Li, M.R.T. Arruda, A. Pagani, Yen‐Ping Chu, Cheng‐Chi Lee and Erasmo Carrera. Their work appears in journals such as IEEE Transactions on Image Processing, IEEE Access and Sensors.
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.