TAI-SARNET: Deep Transferred Atrous-Inception CNN for Small Samples SAR ATR

TAI-SARNET: Deep Transferred Atrous-Inception CNN for Small Samples SAR ATR

Since Synthetic Aperture Radar (SAR) targets are full of coherent speckle noise, the traditional deep learning models are difficult to effectively extract key features of the targets and share high computational complexity. To solve the problem, an effective lightweight Convolutional Neural Network...

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Bibliographic Details
Main Authors: Zilu Ying, Chen Xuan, Yikui Zhai, Bing Sun, Jingwen Li, Wenbo Deng, Chaoyun Mai, Faguan Wang, Ruggero Donida Labati, Vincenzo Piuri, Fabio Scotti
Format: Article
Language:English
Published: MDPI AG 2020-03-01
Series:Sensors
Subjects:
synthetic aperture radar (sar)
convolutional neural network (cnn)
transfer learning
atrous-inception module
lightweight network
small sample
Online Access:https://www.mdpi.com/1424-8220/20/6/1724

Internet

https://www.mdpi.com/1424-8220/20/6/1724

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