@inproceedings{de1b4902f7fe4cdf9cd13bf72028c80f,
title = "Zero-shot Learning with Cross-Layer Neural Network for Emitter Pattern Recognition",
abstract = "The existing emitter pattern recognition methods depend on a large number of labeled samples and are unable to handle unknown samples. Zero-shot Learning (ZSL) can migrate from source classes to target categories by learning a common embedding space, thus realizing the generalization to unknown samples. In this paper, a novel Cross-Layer Neural Network (CLNN) is proposed that integrates different embedding methods into an end-to-end deep learning architecture. The experimental results demonstrate that the proposed method can achieve excellent performances in the presence of unseen radar patterns with either new feature combinations or new feature ranges.",
keywords = "Cross-Layer Neural Network, Emitter Pattern Recognition, Zero-shot Learning",
author = "Zilin Zhang and Yan Li and Jinliang Bai",
note = "Publisher Copyright: {\textcopyright} 2019 IEEE.; 2019 IEEE International Conference on Signal, Information and Data Processing, ICSIDP 2019 ; Conference date: 11-12-2019 Through 13-12-2019",
year = "2019",
month = dec,
doi = "10.1109/ICSIDP47821.2019.9172905",
language = "English",
series = "ICSIDP 2019 - IEEE International Conference on Signal, Information and Data Processing 2019",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
booktitle = "ICSIDP 2019 - IEEE International Conference on Signal, Information and Data Processing 2019",
address = "United States",
}