Global Polarimetric Synthetic Aperture Radar Image Segmentation with Data Augmentation and Hybrid Architecture Model

Global Polarimetric Synthetic Aperture Radar Image Segmentation with Data Augmentation and Hybrid Architecture Model

Machine learning and deep neural networks have shown satisfactory performance in the supervised classification of Polarimetric Synthetic Aperture Radar (PolSAR) images. However, the PolSAR image classification task still faces some challenges. First, the current form of model input used for this tas...

Ausführliche Beschreibung

Bibliographische Detailangaben
Hauptverfasser: Zehua Wang, Zezhong Wang, Xiaolan Qiu, Zhe Zhang
Format: Artikel
Sprache:English
Veröffentlicht: MDPI AG 2024-01-01
Schriftenreihe:Remote Sensing
Schlagworte:
PolSAR image
land cover classification
hybrid architecture
cross-layer attention
data augmentation
Online Zugang:https://www.mdpi.com/2072-4292/16/2/380

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https://www.mdpi.com/2072-4292/16/2/380

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