Hyperspectral image classification using two-channel deep convolutional neural network

Abstract

Performance of hyperspectral image classification depends on feature extraction. Compared with conventional hand-crafted feature extraction, deep learning can learn feature with more discriminative information. In this paper, a two-channel deep convolutional neural network (Two-CNN) is proposed to learn jointly spectral-spatial feature from hyperspectral… (More)
DOI: 10.1109/IGARSS.2016.7730324

Topics

2 Figures and Tables

Cite this paper

@article{Yang2016HyperspectralIC, title={Hyperspectral image classification using two-channel deep convolutional neural network}, author={Jingxiang Yang and Yongqiang Zhao and Jonathan Cheung-Wai Chan and Chen Yi}, journal={2016 IEEE International Geoscience and Remote Sensing Symposium (IGARSS)}, year={2016}, pages={5079-5082} }