Land-cover classification with high-resolution remote sensing images using transferable deep models

In recent years, large amount of high spatial-resolution remote sensing (HRRS) images are available for land-cover mapping. However, due to the complex information brought by the increased spatial resolution and the data disturbances caused by different conditions of image acquisition, it is often d...

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Veröffentlicht in:	Remote sensing of environment Jg. 237; S. 111322
Hauptverfasser:	Tong, Xin-Yi, Xia, Gui-Song, Lu, Qikai, Shen, Huanfeng, Li, Shengyang, You, Shucheng, Zhang, Liangpei
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	New York Elsevier Inc 01.02.2020 Elsevier BV
Schlagworte:	Artificial neural networks Classification Datasets Deep learning Detection Gaofen-2 satellite images High resolution High-resolution remote sensing Image acquisition Image classification Image resolution Image segmentation Internet Labels Land cover land-cover classification Mapping Neural networks Remote sensing Satellite imagery Spatial data Spatial resolution Target recognition Deep learning High-resolution remote sensing land-cover classification Gaofen-2 satellite images
ISSN:	0034-4257, 1879-0704
Online-Zugang:	Volltext
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