Foliage-Concealed Target Change Detection Scheme Based on Convolutional Neural Network in Low-Frequency Ultrawideband SAR Images

Foliage-Concealed Target Change Detection Scheme Based on Convolutional Neural Network in Low-Frequency Ultrawideband SAR Images

The low-frequency ultrawideband synthetic aperture radar (UWB SAR) has the ability of the foliage-penetrating and high-resolution imaging, which can detect the foliage-concealed target. However, due to low-frequency UWB SAR characteristics and forest detection environments, there are usually some no...

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Bibliographic Details
Main Authors: Hongtu Xie, Yuanjie Zhang, Jinfeng He, Shiliang Yi, Lin Zhang, Nannan Zhu
Format: Article
Language:English
Published: IEEE 2024-01-01
Series:IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
Subjects:
Convolutional neural network (CNN)
foliage-concealed target
low-frequency
synthetic aperture radar (SAR)
target change detection
ultrawideband (UWB)
Online Access:https://ieeexplore.ieee.org/document/10712645/

Internet

https://ieeexplore.ieee.org/document/10712645/

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