<monospace>CroMoDa</monospace>: Unsupervised Oriented SAR Ship Detection via Cross-Modality Distribution Alignment

Most state-of-the-art synthetic aperture radar (SAR) ship detection methods based on deep learning require large amounts of labeled data for network training. However, the annotation process requires significant manpower and resources especially for SAR images, since relevant background knowledge sh...

Ausführliche Beschreibung

Bibliografische Detailangaben

Hauptverfasser:	Xi Chen, Zhirui Wang, Wenhao Wang, Xinyi Xie, Jian Kang, Ruben Fernandez-Beltran
Format:	Artigo
Sprache:	Inglês
Veröffentlicht:	IEEE 2024-01-01
Schriftenreihe:	IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
Schlagworte:	Cross modality synthetic aperture radar (SAR) synthetic aperture radar ship detection transfer learning unsupervised object detection
Online-Zugang:	https://ieeexplore.ieee.org/document/10578309/
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