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...

Ausführliche Beschreibung

Bibliographische Detailangaben

Veröffentlicht in:	IEEE International Geoscience and Remote Sensing Symposium proceedings S. 854 - 857
Hauptverfasser:	Tian, S.R., Wang, C., Zhang, H.
Format:	Tagungsbericht
Sprache:	Englisch
Veröffentlicht:	IEEE 01.07.2017
Schlagworte:	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-Zugang:	Volltext
Tags:	Tag hinzufügen Keine Tags, Fügen Sie den ersten Tag hinzu!