Target Classification in Synthetic Aperture Radar Images Using Quantized Wavelet Scattering Networks

Target Classification in Synthetic Aperture Radar Images Using Quantized Wavelet Scattering Networks

The need to classify targets and features in high-resolution imagery is of interest in applications such as detection of landmines in ground penetrating radar and tumors in medical ultrasound images. Convolutional neural networks (CNNs) trained using extensive datasets are being investigated recentl...

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Bibliographic Details
Main Authors: Raghu G. Raj, Maxine R. Fox, Ram M. Narayanan
Format: Article
Language:English
Published: MDPI AG 2021-07-01
Series:Sensors
Subjects:
adaptive wavelet scattering network
backpropagation
classification
convolutional neural networks
MSTAR
synthetic aperture radar
Online Access:https://www.mdpi.com/1424-8220/21/15/4981

Internet

https://www.mdpi.com/1424-8220/21/15/4981

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