@inproceedings{21e0f4f854a241779f2383893fac67a9,
title = "Manifold learning based supervised hyperspectral data classification method using class encoding",
abstract = "Manifold learning based unsupervised classification methods will be unable to obtain satisfactory results because of the lack of training samples. The employment of training samples' information makes manifold learning based classification become supervised, and thus brings the improvement on classification accuracy. In order to make full use of this information, we emphatically consider the hyperspectral data distribute by clusters. A novel supervised manifold learning method termed class encoding is proposed for hyperspectral data classification. The experimental results show that this algorithm has better classification performance than the existing supervised manifold learning algorithm.",
keywords = "class encoding, hyperspectral data, manifold learning, supervised classification",
author = "Zhang Miao and Guo Wei and Cui Yiming and Shen Fei and Shen Yi",
note = "Publisher Copyright: {\textcopyright} 2016 IEEE.; 36th IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2016 ; Conference date: 10-07-2016 Through 15-07-2016",
year = "2016",
month = nov,
day = "1",
doi = "10.1109/IGARSS.2016.7729817",
language = "英语",
series = "International Geoscience and Remote Sensing Symposium (IGARSS)",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "3160--3163",
booktitle = "2016 IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2016 - Proceedings",
address = "美国",
}