96 citations · 245 across the 21 of their papers we have counts for
6 papers · 1 filter
MultiScale Spectral-Spatial Convolutional Transformer for Hyperspectral Image Classification
Zhiqiang Gong, Xian Zhou, Wen Yao
Due to the powerful ability in capturing the global information, Transformer has become an alternative architecture of CNNs for hyperspectral image classification. However, general…
Deep Intrinsic Decomposition with Adversarial Learning for Hyperspectral Image Classification
Zhiqiang Gong, Xian Zhou, Wen Yao
Convolutional neural networks (CNNs) have been demonstrated their powerful ability to extract discriminative features for hyperspectral image classification. However, general deep…
Multi-fidelity prediction of fluid flow and temperature field based on transfer learning using Fourier Neural Operator
Yanfang Lyu, Xiaoyu Zhao, Zhiqiang Gong +2
Data-driven prediction of fluid flow and temperature distribution in marine and aerospace engineering has received extensive research and demonstrated its potential in real-time pr…
Uncertainty Guided Ensemble Self-Training for Semi-Supervised Global Field Reconstruction
Yunyang Zhang, Zhiqiang Gong, Xiaoyu Zhao +1
Recovering a globally accurate complex physics field from limited sensor is critical to the measurement and control in the aerospace engineering. General reconstruction methods for…
RecFNO: a resolution-invariant flow and heat field reconstruction method from sparse observations via Fourier neural operator
Xiaoyu Zhao, Xiaoqian Chen, Zhiqiang Gong +3
Perception of the full state is an essential technology to support the monitoring, analysis, and design of physical systems, one of whose challenges is to recover global field from…
Multi-fidelity surrogate modeling for temperature field prediction using deep convolution neural network
Yunyang Zhang, Zhiqiang Gong, Weien Zhou +3
Temperature field prediction is of great importance in the thermal design of systems engineering, and building the surrogate model is an effective way for the task. Generally, larg…