no code implementations • RANLP 2021 • Yikuan Xie, Wenyong Wang, Mingqian Du, Qing He
It has been widely recognized that syntax information can help end-to-end neural machine translation (NMT) systems to achieve better translation.
no code implementations • 22 Dec 2023 • Liwei Hu, Wenyong Wang, Yu Xiang, Stefan Sommer
The aerodynamic coefficients of aircrafts are significantly impacted by its geometry, especially when the angle of attack (AoA) is large.
no code implementations • 14 Jun 2023 • Haoming Li, Yu Xiang, Haodong Xu, Wenyong Wang
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.
no code implementations • 10 May 2023 • Xiaorui Bai, Wenyong Wang, Jun Zhang, Yueqing Wang, Yu Xiang
Flow field segmentation and classification help researchers to understand vortex structure and thus turbulent flow.
no code implementations • 17 Oct 2022 • Zihao Chen, Wenyong Wang, Sai Zou
The novel model enables VAE to adjust the parameter capacity to divide dependent and independent data features flexibly.
no code implementations • 23 Jun 2022 • Yu Xiang, Guangbo Zhang, Liwei Hu, Jun Zhang, Wenyong Wang
Geometrical shape of airfoils, together with the corresponding flight conditions, are crucial factors for aerodynamic performances prediction.
no code implementations • 23 Mar 2022 • Yu Xiang, Yu Huang, Haodong Xu, Guangbo Zhang, Wenyong Wang
The identification of pedestrians using radar micro-Doppler signatures has become a hot topic in recent years.
no code implementations • 22 Apr 2021 • Rajesh Kumar, Wenyong Wang, Cheng Yuan, Jay Kumar, Zakria, He Qing, Ting Yang, Abdullah Aman Khan
To solve this challenging task, we propose a blockchain-based federated learning framework that provides collaborative data training solutions by coordinating multiple hospitals to train and share encrypted federated models without leakage of data privacy.
no code implementations • 26 Feb 2021 • Rajesh Kumar, Wenyong Wang, Jay Kumar, Zakria, Ting Yang, Waqar Ali
Specifically for malware detection task, (i) we propose a novel user (local) neural network (LNN) which trains on local distribution and (ii) then to assure the model authenticity and quality, we propose a novel smart contract which enable aggregation process over blokchain platform.
no code implementations • 11 Aug 2020 • Liwei Hu, Wenyong Wang, Yu Xiang, Jun Zhang
Motivated by the problems of existing approaches and inspired by the success of the generative adversarial networks (GANs) in the field of computer vision, we prove an optimal discriminator theorem that the optimal discriminator of a GAN is a radial basis function neural network (RBFNN) while dealing with nonlinear sparse FFD regression and generation.
1 code implementation • 10 Jul 2020 • Rajesh Kumar, Abdullah Aman Khan, Sinmin Zhang, Jay Kumar, Ting Yang, Noorbakhash Amiri Golalirz, Zakria, Ikram Ali, Sidra Shafiq, Wenyong Wang
Blockchain technology authenticates the data and federated learning trains the model globally while preserving the privacy of the organization.