Change detection based on deep feature representation and mapping transformation for multi-spatial-resolution remote sensing images

Multi-spatial-resolution change detection is a newly proposed issue and it is of great significance in remote sensing, environmental and land use monitoring, etc. Though multi-spatial-resolution image-pair are two kinds of representations of the same reality, they are often incommensurable superfici...

Celý popis

Uložené v:

Podrobná bibliografia
Vydané v:	ISPRS journal of photogrammetry and remote sensing Ročník 116; s. 24 - 41
Hlavní autori:	Zhang, Puzhao, Gong, Maoguo, Su, Linzhi, Liu, Jia, Li, Zhizhou
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	Elsevier B.V 01.06.2016
Predmet:	Change detection Construction contracts data collection Deep neural networks Denoising autoencoder Feature transformation land use Mapping monitoring Neural networks Remedies Remote sensing Representations Segmentation Spatial-resolution Stacked denoising autoencoder Denoising autoencoder Deep neural networks Feature transformation Change detection Stacked denoising autoencoder Spatial-resolution
ISSN:	0924-2716, 1872-8235
On-line prístup:	Získať plný text
Tagy:	Pridať tag Žiadne tagy, Buďte prvý, kto otaguje tento záznam!

Buďte prvý, kto okomentuje tento záznam!