[1] Sasikala J. Ship detection and recognition for offshore and inshore applications: A survey［J］. International Journal of Intelligent Unmanned Systems, 2019, 7(4): 177-188.

[2] Bo L I, Xiaoyang X I E, Xingxing W E I, et al. Ship detection and classification from optical remote sensing images: A survey［J］. Chinese Journal of Aeronautics, 2021, 34(3): 145-163.

[3] 刘中, 苏鹏. 民船遂行军事运输任务时海事安全监管问题研究［J］. 综合运输, 2017, 39(1): 32-36. LIU Zhong, SU Peng. Research on maritime safety supervision issues when civilian ships perform military transportation missions［J］. China Transportation Review, 2017, 39(1): 32-36.

[4] Svilicic B, Kamahara J, Rooks M, et al. Maritime cyber risk management: An experimental ship assessment［J］. The Journal of Navigation, 2019, 72(5): 1108-1120.

[5] Chaturvedi S K, Yang C S, Ouchi K, et al. Ship recognition by integration of SAR and AIS［J］. The Journal of Navigation, 2012, 65(2): 323-337.

[6] Song J, Wang Y, Chen W, et al. Radar HRRP recognition based on CNN［J］. The Journal of Engineering, 2019, 2019(21): 7766-7769.

[7] El Housseini A, Toumi A, Khenchaf A. Deep Learning for target recognition from SAR images［C］//2017 seminar on detection systems architectures and technologies (DAT). IEEE, 2017: 1-5.

[8] 李勇, 王德功, 常硕, 等. 一种 SAR 图像特征提取和目标分类的新方法［J］. 现代防御技术, 2013, 41(4): 126-130. LI Yong, Wang De-gong, CHANG Shuo, et al. A new method for SAR image feature extraction and object classification［J］. Modern Defense Technology, 2013, 41(4): 126-130.

[9] Xiao F, Ligteringen H, Van Gulijk C, et al. Comparison study on AIS data of ship traffic behavior［J］. Ocean Engineering, 2015, 95: 84-93.

[10] 常吉亮, 谢磊, 魏志威, 等. 基于深度卷积神经网络的船舶轨迹分类研究［J］. 武汉理工大学学报(交通科学与工程版), 2022, (1): 046. CHANG Ji-liang, XIE Lei, WEI Zhi-wei, et al. Research on ship trajectory classification based on deep convolutional neural network［J］. Journal of Wuhan University of Technology (Transportation Science & Engineering), 2022, (1): 046.

[11] 梁海涛, 张学礼, 童创明, 等. 基于小波分解与方位角平均 HRRP 的 SVM 目标识别方法［J］. 数据采集与处理, 2010, 25(1): 29-32. LIANG Hai-tao, ZHANG Xue-li, TONG Chuang-ming, et al. SVM target recognition method based on wavelet decomposition and azimuth average HRRP［J］. Journal of Data Acquisition and Processing, 2010, 25(1): 29-32.

[12] 赵文强, 孙巍. 基于S4-YOLO的海上目标检测识别方法［J］. 光学与光电技术, 2020, 18(4): 38-46. ZHAO Wen-qiang, SUN Wei. Detection and recognition method of marine target based on S4-YOLO［J］. Optics & Optoelectronic Technology, 2020, 18(4): 38-46.

[13] 刘仕彦, 张智杰, 雷波. 基于BP-Net网络结构的图像去雾算法研究［J］. 光学与光电技术, 2020, 18(6): 46-52. LIU Shi-yan, ZHANG Zhi-jie, LEI Bo. Image dehazing algorithm based on BP-Net network structure［J］. Optics & Optoelectronic Technology, 2020, 18(6): 46-52.

[14] Fürnkranz J, Flach P A. An analysis of rule evaluation metrics［C］//Proceedings of the 20th International Conference on Machine Learning (ICML-03), 2003: 202-209.

[15] Hossin M, Sulaiman M N. A review on evaluation metrics for data classification evaluations［J］. International Journal of Data Mining & Knowledge Management Process, 2015, 5(2): 1.

[16] Wagner S A. SAR ATR by a combination of convolutional neural network and support vector machines［J］. IEEE transactions on Aerospace and Electronic Systems, 2016, 52(6): 2861-2872.

[17] Chen X, Liu Y, Achuthan K, et al. A ship movement classification based on automatic identification system (AIS) data using convolutional neural network［J］. Ocean Engineering, 2020, 218: 108182.

[18] 杨予昊, 孙晶明, 虞盛康, 等. 基于卷积神经网络的高分辨距离像目标识别［J］. 现代雷达, 2017, 39(12): 24-28.YANG Yu-hao, SUN Jin-ming, YU Sheng-kang, et al. High resolution range image target recognition based on convolutional neural network［J］. Modern Radar, 2017, 39(12): 24-28.

[19] Bai Y, Yang E, Han B, et al. Understanding and improving early stopping for learning with noisy labels［J］. Advances in Neural Information Processing Systems, 2021, 34: 24392-24403.