Ship type recognition method based on multi-view learning

Tianjiao Li; Zhonglin Liu; Licai Wang; Jintao Yu

doi:10.1117/12.2684617

21 July 2023 Ship type recognition method based on multi-view learning

Tianjiao Li, Zhonglin Liu, Licai Wang, Jintao Yu

Proceedings Volume 12717, 3rd International Conference on Artificial Intelligence, Automation, and High-Performance Computing (AIAHPC 2023); 127171N (2023) https://doi.org/10.1117/12.2684617
Event: 3rd International Conference on Artificial Intelligence, Automation, and High-Performance Computing (AIAHPC 2023), 2023, Wuhan, China

Abstract

Aiming at the problem of low reliability of ship model recognition from remote sensing images, we propose a ship model recognition method based on multi-view learning. Firstly, the multi-view feature data is constructed by different feature operators. Then the single feature view data is used to train SVM classifier respectively while the multi-view data is fused and used to train classifier by CPM-Nets. Finally, we fuse the results of single feature view classifier and multi-feature view classifier by classifier aggregation to enhance the accuracy rate. Experiments show that the proposed method can improve the accuracy of ship type recognition.

Citation Download Citation

Tianjiao Li, Zhonglin Liu, Licai Wang, and Jintao Yu "Ship type recognition method based on multi-view learning", Proc. SPIE 12717, 3rd International Conference on Artificial Intelligence, Automation, and High-Performance Computing (AIAHPC 2023), 127171N (21 July 2023); https://doi.org/10.1117/12.2684617

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