华中科技大学学报（自然科学版）2024，Vol.52Issue(4)：76-81,6.DOI:10.13245/j.hust.240555
基于多特征聚合的水面遮挡目标检测算法
Multi feature fusion-based water occlusion object detection algorithm
摘要
Abstract
Aiming at the problem that the object detection accuracy was affected by the mutual occlusion of ships that often occured when intelligent ships navigated in inland waterways,a water surface occlusion object detection algorithm based on multi-feature aggregation was proposed.First,a multi-scale sensory field feature fusion structure was set up in the backbone network to fuse the visible area of the occluded ship with the surrounding environment features.Second,a hybrid attention mechanism was added to the backbone network and the feature splicing part of the network to enhance the long-range dependence of the network,and to aggregate the features of the ship's bow and stern.Then,a data resampling strategy was designed to adaptively adjust the sample frequency according to the number of ship categories during the training process to alleviate the serious unevenness of the number of ships in the dataset.Finally,the algorithm was validated.Results show that the algorithm can effectively improve the detection accuracy of surface targets under visual occlusion by aggregating multi-scale features such as the visible area of the occluded ship and the surrounding environment,and by aggregating the long-range features of the bow and the stern of the ship,with an accuracy increase of 3.3%compared with the original algorithm.关键词
智能船舶/遮挡检测/多尺度特征融合/混合注意力机制/数据重采样Key words
intelligent ships/occlusion detection/multi-scale feature fusion structure/hybrid attention mechanism/data resampling分类
信息技术与安全科学引用本文复制引用
冯辉,蒋成鑫,徐海祥,谢磊..基于多特征聚合的水面遮挡目标检测算法[J].华中科技大学学报（自然科学版）,2024,52(4):76-81,6.基金项目
国家重点研发计划资助项目(2019YFB1600600,2019YFB1600604) （2019YFB1600600,2019YFB1600604）
国家自然科学基金资助项目(51979210,51879210) （51979210,51879210）
中央高校基本科研业务费专项资金资助项目(2019Ⅲ040,2019Ⅲ132CG). （2019Ⅲ040,2019Ⅲ132CG）
