A novel approach for unlabeled samples in radiation source identification-Reference-Cited by-同舟云学术

A novel approach for unlabeled samples in radiation source identification

Published:2022-04 Issue:2 Volume:33 Page:354-359
ISSN:1004-4132
Container-title:Journal of Systems Engineering and Electronics
language:
Short-container-title:J. of Syst. Eng. Electron.

Author:

Yang Haifen¹,Zhang Hao¹,Wang Houjun¹,Guo Zhengyang¹

Affiliation:

1. School of Information and Communication Engineering, University of Electronic Science and Technology of China,Chengdu,China,611731

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

General Earth and Planetary Sciences,General Environmental Science

Link

http://xplorestaging.ieee.org/ielx7/5971804/9775056/09775062.pdf?arnumber=9775062

Reference35 articles.

1. Transfer Learning on Convolutional Neural Networks for Dog Identification

2. Deep convolutional neural networks for plane identification on satellite im-agery by exploiting transfer learning with a different optimizer;kamsing;Proceedings of the IEEE International Geoscience and Remote Sensing Symposium,0

3. Semi-Supervised Deep Transfer Learning-Based on Adversarial Feature Learning for Label Limited SAR Target Recognition

4. Combining single shot multibox detector with transfer learning for ship detection using Sentinel-1 images

5. Transfer Learning for Human Activities Classification Using Micro-Doppler Spectrograms

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