@inproceedings{95d764b908d04ba4b39fec91e2de95ae,
title = "Kernel automatic target generation process",
abstract = "Automatic target generation process (ATGP) has been widely used for unsupervised hyperspectral target detection. It implements a succession of orthogonal subspace projections (OSPs) to extract targets of interest without prior knowledge. This paper extends ATGP to a kernel version of ATGP, called kernel ATGP (KATGP) to further deal with linear non-separation problem. It introduces nonlinear kernels to map original data space into a higher dimensional feature space so that ATGP can effectively find.",
author = "Bai Xue and Chen, {Shih Yu} and Chunyuan Yu and Yulei Wang and Lin Wang and Meiping Song and Sen Li and Chang, {Chein I.}",
note = "Publisher Copyright: {\textcopyright} 2017 IEEE.; 37th Annual IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2017 ; Conference date: 23-07-2017 Through 28-07-2017",
year = "2017",
month = dec,
day = "1",
doi = "10.1109/IGARSS.2017.8127034",
language = "English",
series = "International Geoscience and Remote Sensing Symposium (IGARSS)",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "636--639",
booktitle = "2017 IEEE International Geoscience and Remote Sensing Symposium",
address = "United States",
}