Self-Supervised Marine Noise Learning with Sparse Autoencoder Network for Generative Target Magnetic Anomaly Detection

As an effective physical field feature to perceive ferromagnetic targets, magnetic anomaly is widely used in covert marine surveillance tasks. However, its practical usability is affected by the complex marine magnetic noise interference, making robust magnetic anomaly detection (MAD) quite a challe...

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Principais autores:	Shigang Wang, Xiangyuan Zhang, Yifan Zhao, Haozi Yu, Bin Li
Format:	Artigo
Jezik:	Inglês
Izdano:	MDPI AG 2024-09-01
Serija:	Remote Sensing
Teme:	magnetic anomaly detection (MAD) marine noise modeling self-supervised learning (SSL) sparse denoising autoencoder (SDAE)
Online dostop:	https://www.mdpi.com/2072-4292/16/17/3263
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