The Outcome of the 2021 IEEE GRSS Data Fusion Contest - Track DSE: Detection of Settlements Without Electricity

In this article, we elaborate on the scientific outcomes of the 2021 Data Fusion Contest (DFC2021), which was organized by the Image Analysis and Data Fusion Technical Committee of the IEEE Geoscience and Remote Sensing Society, on the subject of geospatial artificial intelligence for social good. T...

Celý popis

Uloženo v:
Podrobná bibliografie
Vydáno v:IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing Ročník 14; s. 12375 - 12385
Hlavní autoři: Ma, Yanbiao, Li, Yuxin, Feng, Kexin, Xia, Yu, Huang, Qi, Zhang, Hongyan, Prieur, Colin, Licciardi, Giorgio, Malha, Hana, Chanussot, Jocelyn, Ghamisi, Pedram, Hansch, Ronny, Yokoya, Naoto
Médium: Journal Article
Jazyk:angličtina
Vydáno: Piscataway IEEE 2021
Institute of Electrical and Electronics Engineers (IEEE)
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Témata:
[SPI.SIGNAL]Engineering Sciences [physics]/Signal and Image processing
Artificial intelligence
Convolutional neural networks
Data integration
Data models
deep learning
Detection
Earth
Electricity
Engineering Sciences
Geophysics. Cosmic physics
Image analysis
image analysis and data fusion
Image processing
land cover change detection
Machine learning
multimodal
Multisensor fusion
Natural environment
Ocean engineering
QC801-809
random forests
Remote sensing
Satellite broadcasting
semantic segmentation
Semantics
Signal and Image processing
Task analysis
TC1501-1800
weak supervision
deep learning
land cover change detection
random forests
multimodal
Convolutional neural networks
image analysis and data fusion
weak supervision
ISSN:1939-1404, 2151-1535
On-line přístup:Získat plný text
Tagy: Přidat tag
Žádné tagy, Buďte první, kdo vytvoří štítek k tomuto záznamu!
Popis
Shrnutí:In this article, we elaborate on the scientific outcomes of the 2021 Data Fusion Contest (DFC2021), which was organized by the Image Analysis and Data Fusion Technical Committee of the IEEE Geoscience and Remote Sensing Society, on the subject of geospatial artificial intelligence for social good. The ultimate objective of the contest was to model the state and changes of artificial and natural environments from multimodal and multitemporal remotely sensed data towards sustainable developments. DFC2021 consisted of two challenge tracks: Detection of settlements without electricity (DSE) and multitemporal semantic change detection. We focus here on the outcome of the DSE track. This article presents the corresponding approaches and reports the results of the best-performing methods during the contest.
Bibliografie:ObjectType-Article-1
SourceType-Scholarly Journals-1
ObjectType-Feature-2
content type line 14
ISSN:1939-1404
2151-1535
DOI:10.1109/JSTARS.2021.3130446