Radar Operation Mode Recognition via Multifeature Residual-and-Shrinkage ConvNet
Radar operation mode recognition holds an increasingly critical place in electronic countermeasure as well as in remote sensing. However, the overlapped waveform parameters pose huge challenges to performing the radar operation mode recognition task in severe electromagnetic environments, particular...
Main Authors: | Yujie Zhang, Weibo Huo, Cui Zhang, Yulin Huang, Jifang Pei, Yin Zhang, Jianyu Yang |
---|---|
Format: | Article |
Language: | English |
Published: |
IEEE
2023-01-01
|
Series: | IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing |
Subjects: | |
Online Access: | https://ieeexplore.ieee.org/document/10154143/ |
Similar Items
-
Wearable Sensor-Based Residual Multifeature Fusion Shrinkage Networks for Human Activity Recognition
by: Fancheng Zeng, et al.
Published: (2024-01-01) -
Multifeature Alignment and Matching Network for SAR and Optical Image Registration
by: Xin Hu, et al.
Published: (2025-01-01) -
A Multifeature Learning and Fusion Network for Facial Age Estimation
by: Yulan Deng, et al.
Published: (2021-07-01) -
Multifeature Fusion Neural Network for Oceanic Phenomena Detection in SAR Images
by: Zhuofan Yan, et al.
Published: (2019-12-01) -
Multi‐function radar work mode recognition based on residual shrinkage reconstruction recurrent neural network
by: Lihong Wang, et al.
Published: (2024-11-01)