15 citations · 32 across the 4 of their papers we have counts for
4 papers
MUC-driven Feature Importance Measurement and Adversarial Analysis for Random Forest
Shucen Ma, Jianqi Shi, Yanhong Huang +2
The broad adoption of Machine Learning (ML) in security-critical fields demands the explainability of the approach. However, the research on understanding ML models, such as Random…
An application of data driven reward of deep reinforcement learning by dynamic mode decomposition in active flow control
Sheng Qin, Shuyue Wang, Jean Rabault +1
This paper focuses on the active flow control (AFC) of the flow over a circular cylinder with synthetic jets through deep reinforcement learning (DRL) by implementing a reward func…
Bias Field Poses a Threat to DNN-based X-Ray Recognition
Binyu Tian, Qing Guo, Felix Juefei-Xu +5
The chest X-ray plays a key role in screening and diagnosis of many lung diseases including the COVID-19. More recently, many works construct deep neural networks (DNNs) for chest…
Adversarial Rain Attack and Defensive Deraining for DNN Perception
Liming Zhai, Felix Juefei-Xu, Qing Guo +5
Rain often poses inevitable threats to deep neural network (DNN) based perception systems, and a comprehensive investigation of the potential risks of the rain to DNNs is of great…