95 citations · 126 across the 10 of their papers we have counts for
11 papers
Explainable AI for Comparative Analysis of Intrusion Detection Models
Pap M. Corea, Yongxin Liu, Jian Wang +2
Explainable Artificial Intelligence (XAI) has become a widely discussed topic, the related technologies facilitate better understanding of conventional black-box models like Random…
NoiseCAM: Explainable AI for the Boundary Between Noise and Adversarial Attacks
Wenkai Tan, Justus Renkhoff, Alvaro Velasquez +7
Deep Learning (DL) and Deep Neural Networks (DNNs) are widely used in various domains. However, adversarial attacks can easily mislead a neural network and lead to wrong decisions.…
Exploring Adversarial Attacks on Neural Networks: An Explainable Approach
Justus Renkhoff, Wenkai Tan, Alvaro Velasquez +7
Deep Learning (DL) is being applied in various domains, especially in safety-critical applications such as autonomous driving. Consequently, it is of great significance to ensure t…
TMHOI: Translational Model for Human-Object Interaction Detection
Lijing Zhu, Qizhen Lan, Alvaro Velasquez +4
Detecting human-object interactions (HOIs) is an intricate challenge in the field of computer vision. Existing methods for HOI detection heavily rely on appearance-based features,…
Blockchain Enabled Secure Authentication for Unmanned Aircraft Systems
Yongxin Liu, Jian Wang, Yingjie Chen +5
The integration of air and ground smart vehicles is becoming a new paradigm of future transportation. A decent number of smart unmanned vehicles or UAS will be sharing the national…
Zero-bias Deep Neural Network for Quickest RF Signal Surveillance
Yongxin Liu, Yingjie Chen, Jian Wang +3
The Internet of Things (IoT) is reshaping modern society by allowing a decent number of RF devices to connect and share information through RF channels. However, such an open natur…
Class-Incremental Learning for Wireless Device Identification in IoT
Yongxin Liu, Jian Wang, Jianqiang Li +2
Deep Learning (DL) has been utilized pervasively in the Internet of Things (IoT). One typical application of DL in IoT is device identification from wireless signals, namely Non-cr…
Zero-bias Deep Learning Enabled Quick and Reliable Abnormality Detection in IoT
Yongxin Liu, Jian Wang, Jianqiang Li +2
Abnormality detection is essential to the performance of safety-critical and latency-constrained systems. However, as systems are becoming increasingly complicated with a large qua…
Machine Learning for the Detection and Identification of Internet of Things (IoT) Devices: A Survey
Yongxin Liu, Jian Wang, Jianqiang Li +2
The Internet of Things (IoT) is becoming an indispensable part of everyday life, enabling a variety of emerging services and applications. However, the presence of rogue IoT device…
Distant Domain Transfer Learning for Medical Imaging
Shuteng Niu, Meryl Liu, Yongxin Liu +2
Medical image processing is one of the most important topics in the field of the Internet of Medical Things (IoMT). Recently, deep learning methods have carried out state-of-the-ar…
Zero-Bias Deep Learning for Accurate Identification of Internet of Things (IoT) Devices
Yongxin Liu, Jian Wang, Jianqiang Li +4
The Internet of Things (IoT) provides applications and services that would otherwise not be possible. However, the open nature of IoT make it vulnerable to cybersecurity threats. E…