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

Uloženo v:

Podrobná bibliografie
Vydáno v:	ISPRS journal of photogrammetry and remote sensing Ročník 116; s. 24 - 41
Hlavní autoři:	Zhang, Puzhao, Gong, Maoguo, Su, Linzhi, Liu, Jia, Li, Zhizhou
Médium:	Journal Article
Jazyk:	angličtina
Vydáno:	Elsevier B.V 01.06.2016
Témata:	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 přístup:	Získat plný text
Tagy:	Přidat tag Žádné tagy, Buďte první, kdo vytvoří štítek k tomuto záznamu!

Buďte první, kdo okomentuje tento záznam!