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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Bibliografiset tiedot

Päätekijät:	Hongtu Xie, Yuanjie Zhang, Jinfeng He, Shiliang Yi, Lin Zhang, Nannan Zhu
Aineistotyyppi:	Artigo
Kieli:	Inglês
Julkaistu:	IEEE 2024-01-01
Sarja:	IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
Aiheet:	Convolutional neural network (CNN) foliage-concealed target low-frequency synthetic aperture radar (SAR) target change detection ultrawideband (UWB)
Linkit:	https://ieeexplore.ieee.org/document/10712645/
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