Building Extraction from Satellite Images Using Mask R-CNN and Swin Transformer
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216305%3A26220%2F24%3APU151204" target="_blank" >RIV/00216305:26220/24:PU151204 - isvavai.cz</a>
Result on the web
<a href="https://ieeexplore.ieee.org/document/10524085/" target="_blank" >https://ieeexplore.ieee.org/document/10524085/</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1109/RADIOELEKTRONIKA61599.2024.10524085" target="_blank" >10.1109/RADIOELEKTRONIKA61599.2024.10524085</a>
Alternative languages
Result language
angličtina
Original language name
Building Extraction from Satellite Images Using Mask R-CNN and Swin Transformer
Original language description
Extracting building footprints from satellite or aerial imagery is critical for many applications. Yet, the precise delineation of buildings from very high spatial resolution remotely sensed images remains challenging. This study investigated the potentiality of using Mask R-CNN based on the Swin Transformer and Feature Pyramid Network (FPN) in extracting building footprints from RGB images in heterogeneous urban landscapes. The Swin Transformer and FPN were used to extract multiscale features. The model's performance was compared with several instance segmentation models based on the ResNet-50 backbone, including Mask scoring R-CNN, YOLCAT, and SOLO. Results showed that the model successfully segmented building footprints with a mAP50 and F-measure of 0.85 and 0.89, respectively, outperformed the evaluated instance segmentation models.
Czech name
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Czech description
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Classification
Type
D - Article in proceedings
CEP classification
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OECD FORD branch
20200 - Electrical engineering, Electronic engineering, Information engineering
Result continuities
Project
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Continuities
S - Specificky vyzkum na vysokych skolach
Others
Publication year
2024
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Article name in the collection
2024 34th International Conference Radioelektronika (RADIOELEKTRONIKA)
ISBN
979-8-3503-6216-9
ISSN
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e-ISSN
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Number of pages
5
Pages from-to
„“-„“
Publisher name
Institute of Electrical and Electronics Engineers Inc.
Place of publication
neuveden
Event location
Žilina, Slovakia
Event date
Apr 17, 2024
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
001229165000030