Mingliang Gao
Biographic Data
| ID | 7260203 |
|---|---|
| NAME | Mingliang Gao |
| GIVEN NAMES | Mingliang |
| FAMILY NAME | Gao |
| SIGNATURE | GAO M |
| AFFILIATIONS | Shandong University of Technology |
| ORCID | 0000-0002-8871-6999 |
| VERIFIED | Yes |
| TOTAL WORKS | 8 |
| TOTAL CITATIONS | 0 |
| AUTHOR COUNT | 8 |
| EDITOR COUNT | 0 |
| FIRST PUBLICATION YEAR | 2019 |
| LATEST PUBLICATION YEAR | 2026 |
| H-INDEX | 0 |
Federated Learning-Driven Face Forgery Detection via Rich Feature Complementary Fusion
The rapid expansion of cyber–physical–social systems (CPSSs) highlights the critical need for authentic digital interactions. However, this progress is threatened by deepfake technology, which can undermine system security and trust. Existing deepfake detection models, while effective, typically require centralized data and thus create significant privacy and security vulnerabilities. Furthermore, their reliance on single-modal RGB data limits th…
Space–Frequency and Global–Local Attentive Networks for Sequential Deepfake Detection
The widespread misinformation generated by deepfake systems has emerged as a significant challenge in the dynamic realm of digital media. It poses threats to credibility, privacy, and security of information in daily life. Moreover, the increasing accessibility to facial editing tools further enables users to alter facial characteristics subtly through a series of intricate steps. To address the issue, we introduce a space–frequency and global–lo…
Context-Aware Deepfake Detection for Securing AI-Driven Financial Transactions
The rapid advancement of deepfake technology has threatened the community’s sense of security, particularly in the context of face-based payment systems. Thus, deepfake detection has emerged as a critical issue demanding immediate attention. However, the generalization performance of existing detection models is limited as they are overly reliant on specific forged features while ignoring the common forged features. To address this problem, we in…
Defending Deepfakes by Saliency-Aware Attack
With the rapid development of deep learning, especially the generative adversarial network (GAN), face modification has been substantially advanced and enables the generated images to look more realistic. Given an image or a video frame of a person, such a system can create fake images, which manipulates the movement, expression, and even appearance, e.g., hair color, eye color, and age. Such a system is termed Deepfake, which has raised signific…
A Trust-Aware and Authentication-Based Collaborative Method for Resource Management of Cloud-Edge Computing in Social Internet of Things
The Social Internet of Things (S-IoT) paradigm is focused on topic of the Internet of Things (IoT), which accelerates the object issues by working with the concept of social networks. Searching and finding a new object in the community are considered to manage the number of friends and complex relationships between them and affect the ability to navigate at the cloud-edge layer, and resources, such as battery lifetime of S-IoT devices and energy …
Mechanism investigation of Shi-Xiao-San in treating blood stasis syndrome based on network pharmacology, molecular docking and in vitro/vivo pharmacological validation
Evaluation of Vegf mediated pro-angiogenic and hemostatic effects and chemical marker investigation for Typhae Pollen and its processed product
Monitoring Differential Subsidence along the Beijing–Tianjin Intercity Railway with Multiband SAR Data
High-speed railways have strict standards of infrastructure deformation and post-construction settlement. The interferometric synthetic aperture radar (InSAR) has the ability to detect ground deformation with a high accuracy and wide coverage and is becoming a useful tool for monitoring railway health. In this study, we analyzed the Beijing-Tianjin Intercity Railway (BTIR) track using InSAR time-series analysis with different data sets. First, by…
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Monitoring Differential Subsidence along the Beijing–Tianjin Intercity Railway with Multiband SAR Data
High-speed railways have strict standards of infrastructure deformation and post-construction settlement. The interferometric synthetic aperture radar (InSAR) has the ability to detect ground deformation with a high accuracy and wide coverage and is becoming a useful tool for monitoring railway health. In this study, we analyzed the Beijing-Tianjin Intercity Railway (BTIR) track using InSAR time-series analysis with different data sets. First, by…
Evaluation of Vegf mediated pro-angiogenic and hemostatic effects and chemical marker investigation for Typhae Pollen and its processed product
Mechanism investigation of Shi-Xiao-San in treating blood stasis syndrome based on network pharmacology, molecular docking and in vitro/vivo pharmacological validation
Defending Deepfakes by Saliency-Aware Attack
With the rapid development of deep learning, especially the generative adversarial network (GAN), face modification has been substantially advanced and enables the generated images to look more realistic. Given an image or a video frame of a person, such a system can create fake images, which manipulates the movement, expression, and even appearance, e.g., hair color, eye color, and age. Such a system is termed Deepfake, which has raised signific…
A Trust-Aware and Authentication-Based Collaborative Method for Resource Management of Cloud-Edge Computing in Social Internet of Things
The Social Internet of Things (S-IoT) paradigm is focused on topic of the Internet of Things (IoT), which accelerates the object issues by working with the concept of social networks. Searching and finding a new object in the community are considered to manage the number of friends and complex relationships between them and affect the ability to navigate at the cloud-edge layer, and resources, such as battery lifetime of S-IoT devices and energy …
Space–Frequency and Global–Local Attentive Networks for Sequential Deepfake Detection
The widespread misinformation generated by deepfake systems has emerged as a significant challenge in the dynamic realm of digital media. It poses threats to credibility, privacy, and security of information in daily life. Moreover, the increasing accessibility to facial editing tools further enables users to alter facial characteristics subtly through a series of intricate steps. To address the issue, we introduce a space–frequency and global–lo…
Context-Aware Deepfake Detection for Securing AI-Driven Financial Transactions
The rapid advancement of deepfake technology has threatened the community’s sense of security, particularly in the context of face-based payment systems. Thus, deepfake detection has emerged as a critical issue demanding immediate attention. However, the generalization performance of existing detection models is limited as they are overly reliant on specific forged features while ignoring the common forged features. To address this problem, we in…
Federated Learning-Driven Face Forgery Detection via Rich Feature Complementary Fusion
The rapid expansion of cyber–physical–social systems (CPSSs) highlights the critical need for authentic digital interactions. However, this progress is threatened by deepfake technology, which can undermine system security and trust. Existing deepfake detection models, while effective, typically require centralized data and thus create significant privacy and security vulnerabilities. Furthermore, their reliance on single-modal RGB data limits th…
Computer Science (5 works) · Computer security (4 works) · Artificial Intelligence (3 works) · Generative Adversarial Networks and Image Synthesis (3 works) · Biochemistry (2 works) · Chemistry (2 works) · Digital Media Forensic Detection (2 works) · Medicine (2 works) · Pharmacology (2 works) · Adversarial Robustness in Machine Learning (1 works)