Pengpeng Yang

492 total citations
13 papers, 241 citations indexed

About

Pengpeng Yang is a scholar working on Computer Vision and Pattern Recognition, Law and Information Systems. According to data from OpenAlex, Pengpeng Yang has authored 13 papers receiving a total of 241 indexed citations (citations by other indexed papers that have themselves been cited), including 11 papers in Computer Vision and Pattern Recognition, 3 papers in Law and 2 papers in Information Systems. Recurrent topics in Pengpeng Yang's work include Digital Media Forensic Detection (11 papers), Advanced Steganography and Watermarking Techniques (7 papers) and Generative Adversarial Networks and Image Synthesis (5 papers). Pengpeng Yang is often cited by papers focused on Digital Media Forensic Detection (11 papers), Advanced Steganography and Watermarking Techniques (7 papers) and Generative Adversarial Networks and Image Synthesis (5 papers). Pengpeng Yang collaborates with scholars based in China, Italy and Saudi Arabia. Pengpeng Yang's co-authors include Yao Zhao, Rongrong Ni, Alessandro Piva, Wei Zhao, Zhiqiang Fu, Fabrizio Argenti, Jun Yang, Dasara Shullani, Massimo Iuliani and Hairong Qi and has published in prestigious journals such as Sensors, IEEE Transactions on Circuits and Systems for Video Technology and Pattern Recognition Letters.

In The Last Decade

Pengpeng Yang

12 papers receiving 235 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Pengpeng Yang China 8 206 60 34 30 30 13 241
Dasara Shullani Italy 7 332 1.6× 70 1.2× 54 1.6× 30 1.0× 62 2.1× 22 352
Tajuddin Manhar Mohammed United States 5 183 0.9× 63 1.1× 18 0.5× 43 1.4× 9 0.3× 6 229
Massimo Iuliani Italy 9 402 2.0× 62 1.0× 45 1.3× 27 0.9× 85 2.8× 24 422
Myung-Joon Kwon South Korea 7 231 1.1× 91 1.5× 8 0.2× 21 0.7× 26 0.9× 12 288
A. Costanzo Italy 10 424 2.1× 47 0.8× 29 0.9× 23 0.8× 59 2.0× 19 434
Qingxiao Guan China 12 344 1.7× 45 0.8× 8 0.2× 6 0.2× 18 0.6× 27 359
Yunxia Liu China 11 377 1.8× 48 0.8× 17 0.5× 158 5.3× 7 0.2× 26 400
In-Jae Yu South Korea 11 291 1.4× 58 1.0× 7 0.2× 16 0.5× 35 1.2× 18 321
Zhenhua Qu China 8 522 2.5× 22 0.4× 32 0.9× 105 3.5× 90 3.0× 13 536
Masaaki Fujiyoshi Japan 10 382 1.9× 50 0.8× 25 0.7× 48 1.6× 92 406

Countries citing papers authored by Pengpeng Yang

Since Specialization
Citations

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

Fields of papers citing papers by Pengpeng Yang

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Pengpeng Yang

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

All Works

13 of 13 papers shown
1.
Du, Shuang, et al.. (2025). ForensiCam-215K: A Large Scale Image and Video Dataset for Forensic Analysis. Florence Research (University of Florence). 1–5.
2.
Ni, Rongrong, et al.. (2022). Artifacts-Disentangled Adversarial Learning for Deepfake Detection. IEEE Transactions on Circuits and Systems for Video Technology. 33(4). 1658–1670. 55 indexed citations
3.
Yang, Pengpeng. (2021). Dual-Domain Fusion Convolutional Neural Network for Contrast Enhancement Forensics. Entropy. 23(10). 1318–1318. 7 indexed citations
4.
Yan, Ziqing, Pengpeng Yang, Rongrong Ni, Yao Zhao, & Hairong Qi. (2021). CNN-Based Forensic Method on Contrast Enhancement with JPEG Post-Processing. Computers, materials & continua/Computers, materials & continua (Print). 69(3). 3205–3216. 2 indexed citations
5.
Yang, Pengpeng, et al.. (2021). Anti-Forensics of Image Contrast Enhancement Based on Generative Adversarial Network. Security and Communication Networks. 2021. 1–8. 7 indexed citations
6.
Yang, Pengpeng, Massimo Iuliani, Dasara Shullani, et al.. (2020). Efficient Video Integrity Analysis Through Container Characterization. IEEE Journal of Selected Topics in Signal Processing. 14(5). 947–954. 24 indexed citations
7.
Yang, Pengpeng, et al.. (2020). A Survey of Deep Learning-Based Source Image Forensics. Journal of Imaging. 6(3). 9–9. 49 indexed citations
8.
9.
Yang, Pengpeng, Rongrong Ni, & Yao Zhao. (2018). Double JPEG Compression Detection by Exploring the Correlations in DCT Domain. 728–732. 3 indexed citations
10.
Zhao, Wei, et al.. (2018). Security Consideration for Deep Learning-Based Image Forensics. IEICE Transactions on Information and Systems. E101.D(12). 3263–3266. 5 indexed citations
11.
Yang, Pengpeng, et al.. (2018). A New Dataset for Source Identification of High Dynamic Range Images. Sensors. 18(11). 3801–3801. 25 indexed citations
12.
13.
Yang, Pengpeng, Rongrong Ni, Yao Zhao, & Wei Zhao. (2017). Source camera identification based on content-adaptive fusion residual networks. Pattern Recognition Letters. 119. 195–204. 46 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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2026