A Fast Maritime Target Identification Algorithm for Offshore Ship Detection

Abstract

The early warning monitoring capability of a ship detection algorithm is significant for jurisdictional territorial waters and plays a key role in safeguarding the national maritime strategic rights and interests. In this paper, a Fast Maritime Target Identification algorithm, FMTI, is proposed to identify maritime targets rapidly. The FMTI adopts a Single Feature Map Fusion architecture as its encoder, thereby improving its detection performance for varying scales of ship targets, from tiny-scale targets to large-scale targets. The FMTI algorithm has a decent detection accuracy and computing power, according to the mean average precision (mAP) and floating-point operations (FLOPs). The FMTI algorithm is 7% more accurate than YOLOF for the mAP measure, and FMTI’s FLOPs is equal to 98.016 G. The FMTI can serve the demands of marine vessel identification while also guiding the creation of supplemental judgments for maritime surveillance, offshore military defense, and active warning.

Keywords

• YOLOF
• target identification
• maritime identification
• monitoring and early warning