基于深度学习的船舶图像目标检测技术综述

Review of Deep Learning-Based Ship Image Object Detection Technology

为促进深度学习在船舶检测领域的进一步发展,对基于深度学习的目标检测技术的进展进行梳理,对其优点和局限性进行分析和总结,并以典型技术为线索对目前流行的船舶检测算法进行分析。在此基础上,对船舶检测领域常用的评价指标和船舶图像数据集进行介绍,并对当前基于深度学习的船舶检测技术存在的问题和未来的发展方向进行探讨。研究成果可为深度学习在船舶检测领域的应用提供一定参考。

In order to promote the further development of deep learning in the field of ship detection,the progress of deep learning-based object detection techniques in this field is examined.Their advantages and limitations are analyzed and summarized in detail.By focusing on typical techniques,the popular ship detection algorithms currently in use are systematically summarized.On this basis,the commonly used evaluation metrics and ship image datasets in the field of ship detection are introduced,and the existing problems and future development directions of deep learning-based ship detection technologies are discussed.The research results can provide some guidance for the application of deep learning in the field of ship detection.