Ship Recognition Technology Based on Remote Sensing Images and Improved YOLOv5s
The rapid development of aerospace and remote sensing technology has brought a massive amount of high-resolution sea surface ship image information.Due to the complex background en-vironment of remote sensing images,the classical YOLOv5s algorithm is not ideal for detecting and recognizing ship targets.In response to this issue,an improved YOLOv5s model is proposed.First-ly,Copy paste is used for data augmentation.Secondly,a C3Ghost module is constructed to replace the C3 module in the original YOLOv5s to reduce the computation amount of the network.The ex-perimental results show that the improved YOLOv5s model has significantly improved the effec-tiveness of ship target detection and recognition.
remote sensing imageYOLOv5sship targetdetection and recognition
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