Mingfu Xue

1.0k total citations
49 papers, 628 citations indexed

About

Mingfu Xue is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition and Hardware and Architecture. According to data from OpenAlex, Mingfu Xue has authored 49 papers receiving a total of 628 indexed citations (citations by other indexed papers that have themselves been cited), including 27 papers in Artificial Intelligence, 21 papers in Computer Vision and Pattern Recognition and 15 papers in Hardware and Architecture. Recurrent topics in Mingfu Xue's work include Adversarial Robustness in Machine Learning (23 papers), Physical Unclonable Functions (PUFs) and Hardware Security (15 papers) and Integrated Circuits and Semiconductor Failure Analysis (11 papers). Mingfu Xue is often cited by papers focused on Adversarial Robustness in Machine Learning (23 papers), Physical Unclonable Functions (PUFs) and Hardware Security (15 papers) and Integrated Circuits and Semiconductor Failure Analysis (11 papers). Mingfu Xue collaborates with scholars based in China, Australia and United States. Mingfu Xue's co-authors include Weiqiang Liu, Yushu Zhang, Jian Wang, Aiqun Hu, Jian Wang, Weiqiang Liu, Shichang Sun, Chongyan Gu, Máire O׳Neill and Guyue Li and has published in prestigious journals such as PLoS ONE, IEEE Access and Information Sciences.

In The Last Decade

Mingfu Xue

43 papers receiving 608 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Mingfu Xue China 15 334 187 182 162 134 49 628
Yansong Gao Australia 13 452 1.4× 304 1.6× 390 2.1× 69 0.4× 100 0.7× 44 946
Faiq Khalid Austria 14 217 0.6× 204 1.1× 306 1.7× 119 0.7× 65 0.5× 44 586
Sandeep S. Kumar Netherlands 8 180 0.5× 219 1.2× 282 1.5× 77 0.5× 91 0.7× 11 693
Jiliang Zhang China 14 286 0.9× 566 3.0× 532 2.9× 82 0.5× 201 1.5× 40 944
Amr T. Abdel-Hamid Egypt 11 116 0.3× 240 1.3× 161 0.9× 113 0.7× 81 0.6× 29 489
Guy Gogniat France 16 434 1.3× 413 2.2× 212 1.2× 84 0.5× 145 1.1× 83 833
Timo Kasper Germany 8 224 0.7× 171 0.9× 118 0.6× 71 0.4× 84 0.6× 13 362
James B. Wendt United States 13 188 0.6× 306 1.6× 291 1.6× 82 0.5× 86 0.6× 32 649
Josep Balasch Belgium 14 456 1.4× 275 1.5× 224 1.2× 137 0.8× 102 0.8× 38 665
Xuefei Ning China 13 281 0.8× 123 0.7× 420 2.3× 184 1.1× 32 0.2× 44 737

Countries citing papers authored by Mingfu Xue

Since Specialization
Citations

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

Fields of papers citing papers by Mingfu Xue

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Mingfu Xue

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

All Works

20 of 20 papers shown
1.
Xue, Mingfu, Jinlong Fu, Zhiyuan Li, et al.. (2024). A Reinforcement Learning-Based ELF Adversarial Malicious Sample Generation Method. IEEE Journal on Emerging and Selected Topics in Circuits and Systems. 14(4). 743–757. 1 indexed citations
2.
Xue, Mingfu, et al.. (2024). SSAT: Active Authorization Control and User’s Fingerprint Tracking Framework for DNN IP Protection. ACM Transactions on Multimedia Computing Communications and Applications. 20(10). 1–24. 3 indexed citations
3.
4.
5.
Xue, Mingfu, et al.. (2023). Detecting backdoor in deep neural networks via intentional adversarial perturbations. Information Sciences. 634. 564–577. 7 indexed citations
6.
Zhang, Yushu, et al.. (2023). Adaptive 3D Mesh Steganography Based on Feature-Preserving Distortion. IEEE Transactions on Visualization and Computer Graphics. 30(8). 5299–5312. 9 indexed citations
7.
Xue, Mingfu, et al.. (2023). Untargeted Backdoor Attack Against Deep Neural Networks With Imperceptible Trigger. IEEE Transactions on Industrial Informatics. 20(3). 5004–5013. 7 indexed citations
8.
Xue, Mingfu, Xin Wang, Shichang Sun, et al.. (2023). Compression-resistant backdoor attack against deep neural networks. Applied Intelligence. 53(17). 20402–20417. 11 indexed citations
9.
Xue, Mingfu, et al.. (2022). AdvParams: An Active DNN Intellectual Property Protection Technique via Adversarial Perturbation Based Parameter Encryption. IEEE Transactions on Emerging Topics in Computing. 11(3). 664–678. 17 indexed citations
10.
Xue, Mingfu, Yinghao Wu, Shichang Sun, et al.. (2022). PTB: Robust physical backdoor attacks against deep neural networks in real world. Computers & Security. 118. 102726–102726. 24 indexed citations
11.
Xue, Mingfu, Shichang Sun, Yushu Zhang, Jian Wang, & Weiqiang Liu. (2022). Active intellectual property protection for deep neural networks through stealthy backdoor and users’ identities authentication. Applied Intelligence. 52(14). 16497–16511. 17 indexed citations
12.
Zhang, Yushu, et al.. (2022). Localization of Inpainting Forgery With Feature Enhancement Network. IEEE Transactions on Big Data. 9(3). 936–948. 8 indexed citations
13.
Zhang, Yushu, et al.. (2022). PRNU-based Image Forgery Localization with Deep Multi-scale Fusion. ACM Transactions on Multimedia Computing Communications and Applications. 19(2). 1–20. 14 indexed citations
14.
Xue, Mingfu, et al.. (2022). Use the Spear as a Shield: An Adversarial Example Based Privacy-Preserving Technique Against Membership Inference Attacks. IEEE Transactions on Emerging Topics in Computing. 11(1). 153–169. 4 indexed citations
15.
Xue, Mingfu, et al.. (2021). Backdoors hidden in facial features: a novel invisible backdoor attack against face recognition systems. Peer-to-Peer Networking and Applications. 14(3). 1458–1474. 17 indexed citations
16.
Xue, Mingfu, Yushu Zhang, Jian Wang, & Weiqiang Liu. (2021). Intellectual Property Protection for Deep Learning Models: Taxonomy, Methods, Attacks, and Evaluations. IEEE Transactions on Artificial Intelligence. 3(6). 908–923. 37 indexed citations
17.
Xue, Mingfu, et al.. (2020). One-to-N & N-to-One: Two Advanced Backdoor Attacks Against Deep Learning Models. IEEE Transactions on Dependable and Secure Computing. 19(3). 1562–1578. 45 indexed citations
18.
Xue, Mingfu, et al.. (2020). Machine Learning Security: Threats, Countermeasures, and Evaluations. IEEE Access. 8. 74720–74742. 122 indexed citations
19.
Xue, Mingfu, et al.. (2019). SSL: A Novel Image Hashing Technique Using SIFT Keypoints with Saliency Detection and LBP Feature Extraction against Combinatorial Manipulations. Security and Communication Networks. 2019. 1–18. 13 indexed citations
20.
Xue, Mingfu, et al.. (2019). Building an accurate hardware Trojan detection technique from inaccurate simulation models and unlabelled ICs. IET Computers & Digital Techniques. 13(4). 348–359. 9 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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