Cargando…
A Neural Network with Convolutional Module and Residual Structure for Radar Target Recognition Based on High-Resolution Range Profile
In the conventional neural network, deep depth is required to achieve high accuracy of recognition. Additionally, the problem of saturation may be caused, wherein the recognition accuracy is down-regulated with the increase in the number of network layers. To tackle the mentioned problem, a neural n...
Autores principales: | Fu, Zhequan, Li, Shangsheng, Li, Xiangping, Dan, Bo, Wang, Xukun |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2020
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7038176/ https://www.ncbi.nlm.nih.gov/pubmed/31973114 http://dx.doi.org/10.3390/s20030586 |
Ejemplares similares
-
An Application of Analytic Wavelet Transform and Convolutional Neural Network for Radar Intrapulse Modulation Recognition
por: Walenczykowska, Marta, et al.
Publicado: (2023) -
An Adaptive Feature Learning Model for Sequential Radar High Resolution Range Profile Recognition
por: Peng, Xuan, et al.
Publicado: (2017) -
Temporal Convolutional Neural Networks for Radar Micro-Doppler Based Gait Recognition †
por: Addabbo, Pia, et al.
Publicado: (2021) -
Radar Emitter Signal Recognition Based on One-Dimensional Convolutional Neural Network with Attention Mechanism
por: Wu, Bin, et al.
Publicado: (2020) -
Activity recognition of FMCW radar human signatures using tower convolutional neural networks
por: Helen Victoria, A., et al.
Publicado: (2021)