Yun-Qing Shi

790 total citations
19 papers, 603 citations indexed

About

Yun-Qing Shi is a scholar working on Computer Vision and Pattern Recognition, Media Technology and Information Systems. According to data from OpenAlex, Yun-Qing Shi has authored 19 papers receiving a total of 603 indexed citations (citations by other indexed papers that have themselves been cited), including 19 papers in Computer Vision and Pattern Recognition, 3 papers in Media Technology and 2 papers in Information Systems. Recurrent topics in Yun-Qing Shi's work include Advanced Steganography and Watermarking Techniques (18 papers), Digital Media Forensic Detection (18 papers) and Chaos-based Image/Signal Encryption (7 papers). Yun-Qing Shi is often cited by papers focused on Advanced Steganography and Watermarking Techniques (18 papers), Digital Media Forensic Detection (18 papers) and Chaos-based Image/Signal Encryption (7 papers). Yun-Qing Shi collaborates with scholars based in United States, China and South Korea. Yun-Qing Shi's co-authors include Hao‐Tian Wu, Jean‐Luc Dugelay, Jingyu Ye, Jiwu Huang, Jinwei Wang, Ting Li, Shiguo Lian, Guopu Zhu, Shaohua Tang and Jianquan Yang and has published in prestigious journals such as IEEE Transactions on Circuits and Systems for Video Technology, Knowledge-Based Systems and IEEE Transactions on Multimedia.

In The Last Decade

Yun-Qing Shi

18 papers receiving 583 citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Yun-Qing Shi United States 11 527 99 71 35 25 19 603
A. Swaminathan United States 7 628 1.2× 106 1.1× 34 0.5× 48 1.4× 46 1.8× 10 676
Fangjun Huang China 18 1.5k 2.8× 103 1.0× 106 1.5× 76 2.2× 43 1.7× 45 1.5k
Xijian Ping China 15 664 1.3× 50 0.5× 118 1.7× 78 2.2× 33 1.3× 77 724
Yuan‐Gen Wang China 14 519 1.0× 97 1.0× 102 1.4× 79 2.3× 21 0.8× 69 659
Hanqing Zhao China 10 803 1.5× 45 0.5× 217 3.1× 94 2.7× 25 1.0× 19 892
C.-Y. Lin United States 6 501 1.0× 42 0.4× 31 0.4× 60 1.7× 30 1.2× 8 560
Chunfang Yang China 19 1.1k 2.0× 79 0.8× 196 2.8× 75 2.1× 54 2.2× 94 1.2k
François Cayre France 10 602 1.1× 48 0.5× 60 0.8× 57 1.6× 27 1.1× 26 642
Güzin Ulutaş Türkiye 18 777 1.5× 214 2.2× 167 2.4× 111 3.2× 52 2.1× 94 871

Countries citing papers authored by Yun-Qing Shi

Since Specialization
Citations

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

Fields of papers citing papers by Yun-Qing Shi

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Yun-Qing Shi

This figure shows the co-authorship network connecting the top 25 collaborators of Yun-Qing Shi. A scholar is included among the top collaborators of Yun-Qing Shi 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 Yun-Qing Shi. Yun-Qing Shi is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

19 of 19 papers shown
1.
Gao, Guangyong, Shanshan Yang, Xiangyang Hu, Zhihua Xia, & Yun-Qing Shi. (2024). Reversible Data Hiding-Based Local Contrast Enhancement With Nonuniform Superpixel Blocks for Medical Images. IEEE Transactions on Circuits and Systems for Video Technology. 35(2). 1745–1757.
2.
Wang, Jinwei, et al.. (2021). SmsNet: A New Deep Convolutional Neural Network Model for Adversarial Example Detection. IEEE Transactions on Multimedia. 24. 230–244. 25 indexed citations
3.
Xia, Zhiqiu, Xingyuan Wang, Chunpeng Wang, et al.. (2020). Local quaternion polar harmonic Fourier moments-based multiple zero-watermarking scheme for color medical images. Knowledge-Based Systems. 216. 106568–106568. 42 indexed citations
4.
Yoo, Chang D., et al.. (2019). Digital Forensics and Watermarking. Lecture notes in computer science. 4 indexed citations
5.
Yang, Jianhua, Xiangui Kang, Edward K. Wong, & Yun-Qing Shi. (2018). JPEG steganalysis with combined dense connected CNNs and SCA-GFR. Multimedia Tools and Applications. 78(7). 8481–8495. 9 indexed citations
6.
Xuan, Guorong, Xiaolong Li, & Yun-Qing Shi. (2018). Histogram-pair based reversible data hiding via searching for optimal four thresholds. Journal of Information Security and Applications. 39. 58–67. 7 indexed citations
7.
Xuan, Guorong, Xiaolong Li, & Yun-Qing Shi. (2018). Minimum entropy and histogram-pair based JPEG image reversible data hiding. Journal of Information Security and Applications. 45. 1–9. 11 indexed citations
8.
Ding, Feng, et al.. (2018). Smoothing identification for digital image forensics. Multimedia Tools and Applications. 78(7). 8225–8245. 10 indexed citations
9.
Yang, Jianquan, Honglei Ren, Guopu Zhu, Jiwu Huang, & Yun-Qing Shi. (2017). Detecting median filtering via two-dimensional AR models of multiple filtered residuals. Multimedia Tools and Applications. 77(7). 7931–7953. 39 indexed citations
10.
Ye, Jingyu & Yun-Qing Shi. (2017). An effective method to detect seam carving. Journal of Information Security and Applications. 35. 13–22. 9 indexed citations
11.
Kim, Hyoung Joong, et al.. (2017). Digital Forensics and Watermarking. Lecture notes in computer science. 10 indexed citations
12.
Wu, Hao‐Tian, Shaohua Tang, Jiwu Huang, & Yun-Qing Shi. (2017). A novel reversible data hiding method with image contrast enhancement. Signal Processing Image Communication. 62. 64–73. 69 indexed citations
13.
Chen, Beijing, Xiaoming Qi, Xingming Sun, & Yun-Qing Shi. (2017). Quaternion pseudo-Zernike moments combining both of RGB information and depth information for color image splicing detection. Journal of Visual Communication and Image Representation. 49. 283–290. 43 indexed citations
14.
Wang, Jinwei, Ting Li, Yun-Qing Shi, Shiguo Lian, & Jingyu Ye. (2016). Forensics feature analysis in quaternion wavelet domain for distinguishing photographic images and computer graphics. Multimedia Tools and Applications. 76(22). 23721–23737. 134 indexed citations
15.
Shi, Yun-Qing, Hyoung Joong Kim, Fernando Pérez‐González, & Isao Echizen. (2016). Digital-Forensics and Watermarking. Lecture notes in computer science. 7 indexed citations
16.
Gao, Guangyong, et al.. (2016). Reversible Watermarking with Adaptive Embedding Threshold Matrix. KSII Transactions on Internet and Information Systems. 10(9). 1 indexed citations
17.
Feng, Bingwen, Wei Lu, Wei Sun, Jiwu Huang, & Yun-Qing Shi. (2015). Robust image watermarking based on Tucker decomposition and Adaptive-Lattice Quantization Index Modulation. Signal Processing Image Communication. 41. 1–14. 23 indexed citations
18.
Wu, Hao‐Tian, Jean‐Luc Dugelay, & Yun-Qing Shi. (2014). Reversible Image Data Hiding with Contrast Enhancement. IEEE Signal Processing Letters. 22(1). 81–85. 123 indexed citations
19.
Ding, Feng, Guopu Zhu, Jianquan Yang, Jin Xie, & Yun-Qing Shi. (2014). Edge Perpendicular Binary Coding for USM Sharpening Detection. IEEE Signal Processing Letters. 22(3). 327–331. 37 indexed citations

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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