Feb. 12, 2024, 5:45 a.m. | Xiaoxuan Zhang Quan Pan Salvador Garc\'ia

cs.CV updates on arXiv.org arxiv.org

Deep learning (DL)-based sea\textendash land clutter classification for sky-wave over-the-horizon-radar (OTHR) has become a novel research topic. In engineering applications, real-time predictions of sea\textendash land clutter with existing distribution discrepancies are crucial. To solve this problem, this article proposes a novel Multisource Semisupervised Adversarial Domain Generalization Network (MSADGN) for cross-scene sea\textendash land clutter classification. MSADGN can extract domain-invariant and domain-specific features from one labeled source domain and multiple unlabeled source domains, and then generalize these features to an arbitrary unseen …

adversarial applications article become classification cs.cv deep learning distribution domain engineering horizon network novel predictions radar real-time research solve

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