209 citations · 333 across the 11 of their papers we have counts for
13 papers
Improving Air Mobility for Pre-Disaster Planning with Neural Network Accelerated Genetic Algorithm
Kamal Acharya, Alvaro Velasquez, Yongxin Liu +3
Weather disaster related emergency operations pose a great challenge to air mobility in both aircraft and airport operations, especially when the impact is gradually approaching. W…
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…
GraphDAC: A Graph-Analytic Approach to Dynamic Airspace Configuration
Ke Feng, Dahai Liu, Yongxin Liu +2
The current National Airspace System (NAS) is reaching capacity due to increased air traffic, and is based on outdated pre-tactical planning. This study proposes a more dynamic air…
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…
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…
Counter-Unmanned Aircraft System(s) (C-UAS): State of the Art, Challenges and Future Trends
Jian Wang, Yongxin Liu, Houbing Song
Unmanned aircraft systems (UAS), or unmanned aerial vehicles (UAVs), often referred to as drones, have been experiencing healthy growth in the United States and around the world. T…
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…