A Multi-Scale U-Shaped Convolution Auto-Encoder Based on Pyramid Pooling Module for Object Recognition in Synthetic Aperture Radar Images

A Multi-Scale U-Shaped Convolution Auto-Encoder Based on Pyramid Pooling Module for Object Recognition in Synthetic Aperture Radar Images

Although unsupervised representation learning (RL) can tackle the performance deterioration caused by limited labeled data in synthetic aperture radar (SAR) object classification, the neglected discriminative detailed information and the ignored distinctive characteristics of SAR images can lead to...

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Bibliographic Details
Main Authors: Sirui Tian, Yiyu Lin, Wenyun Gao, Hong Zhang, Chao Wang
Format: Article
Language:English
Published: MDPI AG 2020-03-01
Series:Sensors
Subjects:
multi-scale representation learning (msrl)
pyramid pooling module (ppm)
compact depth-wise separable convolution (cseconv)
convolution auto-encoder (cae)
object classification
synthetic aperture radar (sar)
Online Access:https://www.mdpi.com/1424-8220/20/5/1533

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https://www.mdpi.com/1424-8220/20/5/1533

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