[1] Yang Y D, Wang X F, Pan J J. Improved CNN and its application in ship identification[J]. Computer Engineering and Design, 2018, 39(10): 3228-3233. DOI:10.16208/j.issn1000-7024.2018.10.039. (in Chinese)
[2] Vagale A, Oucheikh R, Bye R T, et al. Path planning and collision avoidance for autonomous surface vehicles Ⅰ: A review[J]. Journal of Marine Science and Technology, 2021, 26(4): 1292-1306. DOI: 10.1007/s00773-020-00787-6.
[3] Zhang B, Xu Z F, Zhang J, et al. A warning framework for avoiding vessel-bridge and vessel-vessel collisions based on generative adversarial and dual-task networks[J].Computer-Aided Civil and Infrastructure Engineering, 2022, 37(5): 629-649. DOI: 10.1111/mice.12757.
[4] Cui Z Y, Wang X Y, Liu N Y, et al. Ship detection in large-scale SAR images via spatial shuffle-group enhance attention[J].IEEE Transactions on Geoscience and Remote Sensing, 2021, 59(1): 379-391. DOI: 10.1109/TGRS.2020.2997200.
[5] Ren S Q, He K M, Girshick R, et al. Faster R-CNN: Towards real-time object detection with region proposal networks[J]. IEEE Transactions on Pattern Analysis and Machine Intelligence, 2017, 39(6): 1137-1149. DOI: 10.1109/TPAMI.2016.2577031.
[6] Liu W, Anguelov D, Erhan D, et al. SSD: Single shotmultibox detector[C]//European Conference on Computer Vision. Berlin, Germany, 2016: 21-37. DOI: 10.1007/978-3-319-46448-0_2.
[7] Redmon J, Divvala S, Girshick R, et al. You only look once: Unified, real-time object detection[C]//2016 IEEE Conference on Computer Vision and Pattern Recognition(CVPR). Las Vegas, NV, USA, 2016: 779-788. DOI: 10.1109/CVPR.2016.91.
[8] Shao Z F, Wu W J, Wang Z Y, et al.SeaShips: A large-scale precisely annotated dataset for ship detection[J]. IEEE Transactions on Multimedia, 2018, 20(10): 2593-2604. DOI: 10.1109/TMM.2018.2865686.
[9] Li H, Deng L B, Yang C, et al. Enhanced YOLOv3 tiny network for real-time ship detection from visual image[J].IEEE Access, 2021, 9: 16692-16706. DOI: 10.1109/ACCESS.2021.3053956.
[10] Lee W J, Roh M I, Lee H W, et al. Detection and tracking for the awareness of surroundings of a ship based on deep learning[J]. Journal of Computational Design and Engineering, 2021, 8(5): 1407-1430. DOI: 10.1093/jcde/qwab053.
[11] Ni Y H, Mao J X, Wang H, et al. Toward high-precision crack detection in concrete bridges using deep learning[J].Journal of Performance of Constructed Facilities, 2023, 37(3): 04023017. DOI: 10.1061/jpcfev.cfeng-4275.
[12] Zhou J C, Jiang P, Zou A R, et al. Ship target detection algorithm based on improved YOLOv5[J]. Journal of Marine Science and Engineering, 2021, 9(8): 908-922. DOI: 10.3390/jmse9080908.
[13] Hu J, Shen L, Sun G. Squeeze-and-excitation networks[C]//2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition. Salt Lake City, UT, USA, 2018: 7132-7141. DOI: 10.1109/CVPR.2018.00745.
[14] Xia Y, Chen L M, Wang J J, et al. Single shot multibox detector based vessel detection method and application for active anti-collision monitoring[J]. Journal of Hunan University: Natural Science, 2020, 47(3): 97-105. DOI:10.16339/j.cnki.hdxbzkb.2020.03.012. (in Chinese)
[15] Ni Y H, Lu H, Ji C, et al. Comparative analysis on bridge corrosion damage detection based on semantic segmentation [J]. Journal of Southeast University(Natural Science Edition), 2023, 53(2): 201-209. DOI:10.3969/j.issn.1001-0505.2023.02.003. (in Chinese)