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...

Ausführliche Beschreibung

Gespeichert in:

Bibliographische Detailangaben
Veröffentlicht in:	Remote sensing (Basel, Switzerland) Jg. 11; H. 11; S. 1382
Hauptverfasser:	Peng, Daifeng, Zhang, Yongjun, Guan, Haiyan
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Basel MDPI AG 10.06.2019
Schlagworte:	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
Online-Zugang:	Volltext
Tags:	Tag hinzufügen Keine Tags, Fügen Sie den ersten Tag hinzu!

Schreiben Sie den ersten Kommentar!