人工智能辅助的海洋立体观测与探测

Artificial Intelligence-Assisted Ocean Stereo Observation and Detection

摘要:

海洋立体观测与探测是获取海洋信息的重要手段,是海洋科学研究、环境保护、经济发展的基础。近年来海洋立体观测网络的快速发展带来了观测数据质量与数量的显著提升,进一步推动了海洋信息处理技术从“模型为主”逐步迈向“数据与模型双驱动”的新范式。在这一过程中,人工智能(AI)与海洋信息的交叉融通发挥了重要作用。本文从海洋立体观测和探测两个方面,讨论经典方法的局限性,回顾AI辅助下海洋物理场重建、水下目标检测与水下目标定位的研究新进展,重点阐述AI辅助的海洋立体观测与探测研究中亟需解决的关键科学问题及潜在的解决思路,并展望了该领域未来的发展方向。

Abstract:

Ocean stereo observation and detection are important ways to obtain ocean information, and form the basis for marine scientific research, environmental protection, and economic development. The rapid development of ocean stereo observation networks in recent years has brought significant improvement in the quality and quantity of observation data, and also promoted the paradigm shift of ocean information processing technology from "model-oriented" to "data and model-driven". In this process, the cross-fertilization of artificial intelligence (AI) and ocean information has played an important role. In this paper, we discuss the limitations of classical methods, review new advances in AI-aided ocean physical field reconstruction, underwater target detection and localization, highlight the key scientific problems and potential solutions in AI-aided ocean stereo observation and detection, and look forward to the future development direction of this field.