288 citations · 337 across the 12 of their papers we have counts for
6 papers · 1 filter
Statistical Loss and Analysis for Deep Learning in Hyperspectral Image Classification
Zhiqiang Gong, Ping Zhong, Weidong Hu
Nowadays, deep learning methods, especially the convolutional neural networks (CNNs), have shown impressive performance on extracting abstract and high-level features from the hype…
Deep Manifold Embedding for Hyperspectral Image Classification
Zhiqiang Gong, Weidong Hu, Xiaoyong Du +2
Deep learning methods have played a more and more important role in hyperspectral image classification. However, the general deep learning methods mainly take advantage of the info…
Hyperspectral Image Classification With Context-Aware Dynamic Graph Convolutional Network
Sheng Wan, Chen Gong, Ping Zhong +3
In hyperspectral image (HSI) classification, spatial context has demonstrated its significance in achieving promising performance. However, conventional spatial context-based metho…
Multi-scale Dynamic Graph Convolutional Network for Hyperspectral Image Classification
Sheng Wan, Chen Gong, Ping Zhong +3
Convolutional Neural Network (CNN) has demonstrated impressive ability to represent hyperspectral images and to achieve promising results in hyperspectral image classification. How…
A novel statistical metric learning for hyperspectral image classification
Zhiqiang Gong, Ping Zhong, Weidong Hu +2
In this paper, a novel statistical metric learning is developed for spectral-spatial classification of the hyperspectral image. First, the standard variance of the samples of each…
An End-to-End Joint Unsupervised Learning of Deep Model and Pseudo-Classes for Remote Sensing Scene Representation
Zhiqiang Gong, Ping Zhong, Weidong Hu +2
This work develops a novel end-to-end deep unsupervised learning method based on convolutional neural network (CNN) with pseudo-classes for remote sensing scene representation. Fir…