288 citations · 291 across the 5 of their papers we have counts for
5 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…
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…
Diversity in Machine Learning
Zhiqiang Gong, Ping Zhong, Weidong Hu
Machine learning methods have achieved good performance and been widely applied in various real-world applications. They can learn the model adaptively and be better fit for specia…