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With the vigorous expansion of the global maritime economic sector, it imposes profound ecological pressure and long-term impacts on the marine ecosystem [1]. Consequently, sustainable development has evolved into a core imperative to comply with international maritime sustainability protocols. However, the sustainable advancement of the maritime industry is hindered by multiple prominent challenges, such as vessel-induced pollution and recurrent eco-environmental emergencies. As environmental regulatory frameworks become increasingly stringent and maritime transportation demand surges amid global economic integration, autonomous maritime vessels are more aligned with the strategic objectives of green and intelligent sustainable development. Nevertheless, autonomous ships exhibit high sensitivity to maritime environmental fluctuations, creating an urgent demand for real-time, high-precision SSE to underpin autonomous navigation and intelligent decision-making systems [2]. The sea state denotes the synergistic dynamics of wind-generated waves and swells at a specific spatiotemporal point in the open ocean [3]. It can be quantitatively characterized by key statistical metrics, including significant wave height, peak wave period, and the Joint North Sea Wave Project wave spectrum.

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Attention-Enhanced Cross-Scale Prototype Learning for Imbalanced SSE

  • 章节

  • 发表日期：

    2026年

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  • Xu Cheng,
  • Mengna Liu,
  • Fan Shi,
  • Xiufeng Liu,
  • Houxiang Zhang,
  • Shengyong Chen

摘要

With the vigorous expansion of the global maritime economic sector, it imposes profound ecological pressure and long-term impacts on the marine ecosystem [1]. Consequently, sustainable development has evolved into a core imperative to comply with international maritime sustainability protocols. However, the sustainable advancement of the maritime industry is hindered by multiple prominent challenges, such as vessel-induced pollution and recurrent eco-environmental emergencies. As environmental regulatory frameworks become increasingly stringent and maritime transportation demand surges amid global economic integration, autonomous maritime vessels are more aligned with the strategic objectives of green and intelligent sustainable development. Nevertheless, autonomous ships exhibit high sensitivity to maritime environmental fluctuations, creating an urgent demand for real-time, high-precision SSE to underpin autonomous navigation and intelligent decision-making systems [2]. The sea state denotes the synergistic dynamics of wind-generated waves and swells at a specific spatiotemporal point in the open ocean [3]. It can be quantitatively characterized by key statistical metrics, including significant wave height, peak wave period, and the Joint North Sea Wave Project wave spectrum.