Abstract

AbstractDue to the vast sea area of China, it is not easy for ships to identify and dispatch at sea, so the target recognition of ships has always been the focus of the development of the target recognition and detection technology. However, the traditional methods of ship recognition are slow and not practical. The target recognition technology of remote sensing images based on deep learning makes up for this shortcoming, and the recognition is fast and accurate. In this paper, YOLO V3 deep learning network is used to create a high-precision remote sensing image training and testing data set. YOLO V3 network is trained and tested, and then TX2 module is used as the carrier to design a concise user interface to test the effect of the computer running in the embedded system.KeywordsYOLO V3Ship target recognitionTX2 module

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