A review of the autoencoder and its variants: A comparative perspective from target recognition in synthetic-aperture radar images
G Dong, G Liao, H Liu, G Kuang - IEEE Geoscience and …, 2018 - ieeexplore.ieee.org
In recent years, unsupervised feature learning based on a neural network architecture has
become a hot new topic for research [1]-[4]. The revival of interest in such deep networks can …
become a hot new topic for research [1]-[4]. The revival of interest in such deep networks can …
FEC: A feature fusion framework for SAR target recognition based on electromagnetic scattering features and deep CNN features
The active recognition of interesting targets has been a vital issue for synthetic aperture
radar (SAR) systems. The SAR recognition methods are mainly grouped as follows …
radar (SAR) systems. The SAR recognition methods are mainly grouped as follows …
SAR target recognition via joint sparse representation of monogenic signal
G Dong, G Kuang, N Wang, L Zhao… - IEEE Journal of Selected …, 2015 - ieeexplore.ieee.org
In this paper, the classification via sprepresentation and multitask learning is presented for
target recognition in SAR image. To capture the characteristics of SAR image, a …
target recognition in SAR image. To capture the characteristics of SAR image, a …
Multi-view automatic target recognition using joint sparse representation
H Zhang, NM Nasrabadi, Y Zhang… - IEEE Transactions on …, 2012 - ieeexplore.ieee.org
We introduce a novel joint sparse representation based multi-view automatic target
recognition (ATR) method, which can not only handle multi-view ATR without knowing the …
recognition (ATR) method, which can not only handle multi-view ATR without knowing the …
Adversarial attacks on deep-learning-based SAR image target recognition
T Huang, Q Zhang, J Liu, R Hou, X Wang… - Journal of Network and …, 2020 - Elsevier
Synthetic aperture radar (SAR) image target recognition has consistently been a research
hotspot in the field of radar image interpretation. Compared with traditional target recognition …
hotspot in the field of radar image interpretation. Compared with traditional target recognition …
卷积神经网络模型发展及应用.
严春满， 王铖 - Journal of Frontiers of Computer Science & …, 2021 - search.ebscohost.com
深度学习是机器学习和人工智能研究的最新趋势, 作为一个十余年来快速发展的崭新领域,
越来越受到研究者的关注. 卷积神经网络(CNN) 模型是深度学习模型中最重要的一种经典结构 …
越来越受到研究者的关注. 卷积神经网络(CNN) 模型是深度学习模型中最重要的一种经典结构 …
Classification on the monogenic scale space: Application to target recognition in SAR image
G Dong, G Kuang - IEEE Transactions on Image Processing, 2015 - ieeexplore.ieee.org
This paper introduces a novel classification strategy based on the monogenic scale space
for target recognition in Synthetic Aperture Radar (SAR) image. The proposed method …
for target recognition in Synthetic Aperture Radar (SAR) image. The proposed method …
SAR ATR based on 3D parametric electromagnetic scattering model
W Gongjian, Z Guoqiang, Y Hongcheng, X Mengdao… - 雷达学报, 2017 - radars.ac.cn
Abstract Automatic Target Recognition (ATR) is one of the most difficult problems in
Synthetic Aperture Radar (SAR) data interpretation. In recent years, the model-based SAR …
Synthetic Aperture Radar (SAR) data interpretation. In recent years, the model-based SAR …
[HTML][HTML] 基于三维电磁散射参数化模型的SAR 目标识别方法
文贡坚， 朱国强， 殷红成， 邢孟道， 杨虎， 马聪慧， 闫华… - 雷达学报, 2017 - radars.ac.cn
合成孔径雷达目标识别是雷达数据解译中一个长期研究的难点问题. 近年来, 基于模型的SAR
目标识别方法由于在扩展条件下的识别性能表现良好而备受关注. 在联合国内多家研究单位进行 …
目标识别方法由于在扩展条件下的识别性能表现良好而备受关注. 在联合国内多家研究单位进行 …
Few-shot class-incremental SAR target recognition via cosine prototype learning
Y Zhao, L Zhao, D Ding, D Hu… - IEEE Transactions on …, 2023 - ieeexplore.ieee.org
Recent years have witnessed a remarkable breakthrough in synthetic aperture radar
automatic target recognition (SAR ATR) with the development of deep learning (DL) …
automatic target recognition (SAR ATR) with the development of deep learning (DL) …