Based on the Second-stage Detection Networks to Realize Accurate Detection and Recognition For Anti-ship Missiles

The target detection and recognition technology based on deep learning has high accuracy and speed of target recognition, which is a feasible way to realize the precise strike of anti-ship missiles and the essential way for the development of intelligent combat. Based on the development background of anti-ship missile precision strike and second-stage target detection networks, this paper proposed to achieve accurate detection and recognition of ship targets through Faster R-CNN network, and suggested to achieve maritime multi-targets through Mask R-CNN network. The detection method explored and find a feasible way to achieve the precise strike of anti-ship missiles.