Aiming at the problem of nearshore ship detection in highresolution optical remote sensing images, this paper proposed a port ship target detection method based on a lightweight multi-scale convolutional network. After verification, the method has a good detection effect on port ships. The network improves the feature expression ability without increasing the computational complexity, and can effectively capture rotation-sensitive features, thereby improving the versatility of rotating samples. The average detection rate of all types of ships in the experiment is 96.92%, and the average false alarm rate is 8.54%. High detection rate of ship target can be guaranteed and various false alarm target interference can be effectively eliminated.
Research on a port ship target detection method based on lightweight multi-scale convolutional network
Eighth Symposium on Novel Photoelectronic Detection Technology and Applications ; 2021 ; Kunming,China
Proc. SPIE ; 12169
2022-03-27
Conference paper
Electronic Resource
English
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