Deep Filter Banks for Land-Use Scene Classification

Land-use (LU) scene classification is one of the most challenging tasks in the field of remote sensing (RS) image processing due to its high intraclass variability and low interclass distance. Motivated by the challenge posed by this problem, we propose a novel hybrid architecture, deep filter banks...

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Veröffentlicht in:	IEEE geoscience and remote sensing letters Jg. 13; H. 12; S. 1895 - 1899
Hauptverfasser:	Wu, Hang, Liu, Baozhen, Su, Weihua, Zhang, Wenchang, Sun, Jinggong
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Piscataway IEEE 01.12.2016 The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Schlagworte:	Classification Data acquisition Data models Deep filter banks Encoding Feature extraction Filter banks Filters Fisher vector (FV) Image processing Kernel Land use land-use (LU) scene classification Learning algorithms Machine learning Noise reduction Remote sensing Robustness Semantics stacked denoising sparse autoencoder (SDSAE)
ISSN:	1545-598X, 1558-0571
Online-Zugang:	Volltext
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