End-to-End Change Detection for High Resolution Satellite Images Using Improved UNet

Change detection (CD) is essential to the accurate understanding of land surface changes using available Earth observation data. Due to the great advantages in deep feature representation and nonlinear problem modeling, deep learning is becoming increasingly popular to solve CD tasks in remote-sensi...

Celý popis

Uloženo v:

Podrobná bibliografie
Vydáno v:	Remote sensing (Basel, Switzerland) Ročník 11; číslo 11; s. 1382
Hlavní autoři:	Peng, Daifeng, Zhang, Yongjun, Guan, Haiyan
Médium:	Journal Article
Jazyk:	angličtina
Vydáno:	Basel MDPI AG 10.06.2019
Témata:	Architectural engineering Change detection Coders Datasets Deep learning Earth surface encoder-decoder architecture Encoders-Decoders end-to-end Feature maps High resolution Image detection Image processing Image resolution Image segmentation Information processing International conferences Machine learning multiple side-outputs fusion Neural networks Pattern recognition Remote sensing Satellite imagery Semantic segmentation Semantics United States > US China
ISSN:	2072-4292, 2072-4292
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!