2 citations · 3 across the 8 of their papers we have counts for
8 papers
Diversifying Counterattacks: Orthogonal Exploration for Robust CLIP Inference
Chengze Jiang, Minjing Dong, Xinli Shi +1
Vision-language pre-training models (VLPs) demonstrate strong multimodal understanding and zero-shot generalization, yet remain vulnerable to adversarial examples, raising concerns…
Revisiting Adversarial Training under Hyperspectral Image
Weihua Zhang, Chengze Jiang, Minjing Dong +5
Recent studies have shown that deep learning-based hyperspectral image (HSI) classification models are highly vulnerable to adversarial attacks, posing significant security risks.…
A Review on Zeroing Neural Networks
Chengze Jiang, Jie Gui, Long Jin +1
Zeroing neural networks (ZNNs) have demonstrated outstanding performance on time-varying optimization and control problems. Nonetheless, few studies are committed to illustrating t…
A Survey on Small Sample Imbalance Problem: Metrics, Feature Analysis, and Solutions
Shuxian Zhao, Jie Gui, Minjing Dong +5
The small sample imbalance (S&I) problem is a major challenge in machine learning and data analysis. It is characterized by a small number of samples and an imbalanced class distri…
ColorVein: Colorful Cancelable Vein Biometrics
Yifan Wang, Jie Gui, Xinli Shi +3
Vein recognition technologies have become one of the primary solutions for high-security identification systems. However, the issue of biometric information leakage can still pose…
Survey of Adversarial Robustness in Multimodal Large Language Models
Chengze Jiang, Zhuangzhuang Wang, Minjing Dong +1
Multimodal Large Language Models (MLLMs) have demonstrated exceptional performance in artificial intelligence by facilitating integrated understanding across diverse modalities, in…
Improving Fast Adversarial Training via Self-Knowledge Guidance
Chengze Jiang, Junkai Wang, Minjing Dong +5
Adversarial training has achieved remarkable advancements in defending against adversarial attacks. Among them, fast adversarial training (FAT) is gaining attention for its ability…
Improving Fast Adversarial Training Paradigm: An Example Taxonomy Perspective
Jie Gui, Chengze Jiang, Minjing Dong +4
While adversarial training is an effective defense method against adversarial attacks, it notably increases the training cost. To this end, fast adversarial training (FAT) is prese…