Hierarchical feature exttratction for object recogition in complex SAR image using modified convolutional auto-encoder

Automatic target recognition is a crucial task for SAR remote sensing. Unlike other methods, the unsupervised representation learning based on deep architecture can obtain robust high-level features directly from raw data. A drawback of most unsupervised representation learning methods in SAR ATR is...

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Bibliographic Details

Published in:	IEEE International Geoscience and Remote Sensing Symposium proceedings pp. 854 - 857
Main Authors:	Tian, S.R., Wang, C., Zhang, H.
Format:	Conference Proceeding
Language:	English
Published:	IEEE 01.07.2017
Subjects:	automatic target recognition(ATR) Deep learning Feature extraction Image recognition Kernel Modified convolutional denoising autoencoder (MCSAE) Noise reduction Radar polarimetry Remote sensing Representation learning Stacking Synthetic aperture radar synthetic aperture radar(SAR) Target recognition
ISSN:	2153-7003
Online Access:	Get full text
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