Research on a port ship target detection method based on lightweight multi-scale convolutional network

Xiaoning Hu; ShanJunYu Liu; Zhigang Wu; Zhuo Chen

doi:10.1117/12.2626561

27 March 2022 Research on a port ship target detection method based on lightweight multi-scale convolutional network

Xiaoning Hu, ShanJunYu Liu, Zhigang Wu, Zhuo Chen

Proceedings Volume 12169, Eighth Symposium on Novel Photoelectronic Detection Technology and Applications; 12169B4 (2022) https://doi.org/10.1117/12.2626561
Event: Eighth Symposium on Novel Photoelectronic Detection Technology and Applications, 2021, Kunming, China

Abstract

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.

Citation Download Citation

Xiaoning Hu, ShanJunYu Liu, Zhigang Wu, and Zhuo Chen "Research on a port ship target detection method based on lightweight multi-scale convolutional network", Proc. SPIE 12169, Eighth Symposium on Novel Photoelectronic Detection Technology and Applications, 12169B4 (27 March 2022); https://doi.org/10.1117/12.2626561

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KEYWORDS

Target detection

Convolution

Remote sensing

Detection and tracking algorithms

Feature extraction

Image segmentation

Sensors

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