中国空间科学技术（中英文）2025，Vol.45Issue(1)：153-161,9.DOI:10.16708/j.cnki.1000-758X.2025.0015
遥感船只快速目标检测技术及应用
Fast vessel detection technology for remote sensing application
王海涛 1贺治钧 2周天启 1马岳1
作者信息
- 1. 中国空间技术研究院 卫星应用总体部,北京 100094
- 2. 中国空间技术研究院 通信与导航卫星总体部,北京 100094
- 折叠
摘要
Abstract
Most existing methods have low recognition accuracy for fine-grained remote sensing vessel detection,and the large computation and storage requirements associated with the commonly used floating-point precision data types make it difficult to meet the needs of model in-orbit deployment due to the limited power of on-board devices.To address these challenges,this paper proposed a fast target detection method for fine-grained remote sensing vessels based on model quantization.Firstly,a fusion intelligence-based detection network was designed to solve the problem of"large intra-class differences and small inter-class differences",which can effectively improve the accuracy of fine-grained vessel detection and identification.On this basis,a high-precision model quantization method was proposed to optimize the clipping boundary,which could effectively improve the inference speed.Experimental test results show that the proposed method achieves a maximum accuracy improvement of more than 5.9%compared with existing studies,while the quantization method can achieve a maximum performance improvement of 1.2%.It can effectively reduce the calculation load while maintaining a high accuracy,thus can be easily applied to satellite-based computing units.关键词
卫星遥感船只检测/快速目标检测/CNN模型量化/卫星应用/深度神经网络Key words
satellite remote sensing vessel detection/fast target detection/CNN model quantification/satellite applications/deep neural networks分类
天文与地球科学引用本文复制引用
王海涛,贺治钧,周天启,马岳..遥感船只快速目标检测技术及应用[J].中国空间科学技术（中英文）,2025,45(1):153-161,9.
