3 citations · 3 across the 2 of their papers we have counts for
5 papers
Pedestrian Recognition with Radar Data-Enhanced Deep Learning Approach Based on Micro-Doppler Signatures
Haoming Li, Yu Xiang, Haodong Xu +1
As a hot topic in recent years, the ability of pedestrians identification based on radar micro-Doppler signatures is limited by the lack of adequate training data. In this paper, w…
Novel deep learning methods for 3D flow field segmentation and classification
Xiaorui Bai, Wenyong Wang, Jun Zhang +2
Flow field segmentation and classification help researchers to understand vortex structure and thus turbulent flow. Existing deep learning methods mainly based on global informatio…
A Multi-Characteristic Learning Method with Micro-Doppler Signatures for Pedestrian Identification
Yu Xiang, Yu Huang, Haodong Xu +2
The identification of pedestrians using radar micro-Doppler signatures has become a hot topic in recent years. In this paper, we propose a multi-characteristic learning (MCL) model…
Aerodynamic Data Predictions Based on Multi-task Learning
Liwei Hu, Yu Xiang, Jun Zhan +2
The quality of datasets is one of the key factors that affect the accuracy of aerodynamic data models. For example, in the uniformly sampled Burgers' dataset, the insufficient high…
Flow Field Reconstructions with GANs based on Radial Basis Functions
Liwei Hu, Wenyong Wang, Yu Xiang +1
Nonlinear sparse data regression and generation have been a long-term challenge, to cite the flow field reconstruction as a typical example. The huge computational cost of computat…