[1] Zhang Z L, Zhang Y, Shen Z K. Port recognition in high resolution remote sensing images based on feature spectrum[J]. Acta Electronica Sinica, 38, 2184-2188(2010).

[2] Zhu B, Li J Z, Chen A J. Fast knowledge based recognition of harbor target[J]. Journal of Computer Applications, 26, 729-732(2006).

[3] Chen Q, Wang N, Zhao L J et al. Harbor detection of remote sensing images based on model[C]. //2010 2nd International Conference on Future Computer and Communication, May 21-24, 2010, Wuhan, China., V1-322(2010).

[4] Liu C, Xiao Y Y, Yang J et al. Harbor detection in polarimetric SAR images based on the characteristics of parallel curves[J]. IEEE Geoscience and Remote Sensing Letters, 13, 1400-1404(2016).

[5] LeCun Y, Bengio Y, Hinton G. Deep learning[J]. Nature, 521, 436-444(2015).

[6] Duan Z J, Li S B, Hu J J et al. Review of deep learning based object detection methods and their mainstream frameworks[J]. Laser & Optoelectronics Progress, 57, 120005(2020).

[7] Zhou B, Li R X, Shang Z H et al. Object detection algorithm based on improved Faster R-CNN[J]. Laser & Optoelectronics Progress, 57, 101009(2020).

[8] Dai J F, Li Y, He K M et al. R-FCN: object detection via region-based fully convolutional networks[EB/OL]. (2016-05-20)[2020-10-10]. https://arxiv.org/abs/1605.06409

[9] Wang J L, Lü X Q, Zhang M et al. Remote sensing image ship detection based on improved R-FCN[J]. Laser & Optoelectronics Progress, 56, 162803(2019).

[10] Ghiasi G, Lin T Y, Le Q V. NAS-FPN: learning scalable feature pyramid architecture for object detection[C]. //2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), June 15-20, 2019, Long Beach, CA, USA, 7029-7038(2019).

[11] Cai Z W, Vasconcelos N. Cascade R-CNN: delving into high quality object detection[C]. //2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition, June 18-23, 2018, Salt Lake City, UT, USA, 6154-6162(2018).

[12] Liu Y Q, Feng J K, Xing B W et al. Water surface object detection based on deep learning[J]. Laser & Optoelectronics Progress, 57, 181502(2020).

[13] Liu W, Anguelov D, Erhan D et al. SSD: single shot MultiBox detector[M]. //Leibe B, Matas J, Sebe N, et al. Computer vision-ECCV 2016. Lecture notes in computer science, 9905, 21-37(2016).

[14] Lin T Y, Goyal P, Girshick R et al. Focal loss for dense object detection[C]. //2017 IEEE International Conference on Computer Vision (ICCV), October 22-29, 2017, Venice, Italy., 2999-3007(2017).

[15] Law H, Deng J. CornerNet: detecting objects as paired keypoints[J]. International Journal of Computer Vision, 128, 642-656(2020).

[16] Dai W C, Jin L X, Li G N et al. Real-time airplane detection algorithm in remote-sensing images based on improved YOLOv3[J]. Opto-Electronic Engineering, 45, 84-92(2018).

[17] Dong Y F, Zhang C T, Wang P et al. Airplane detection of optical remote sensing images based on deep learning[J]. Laser & Optoelectronics Progress, 57, 041007(2020).

[18] Chen F, Ren R L, van de Voorde T et al. Fast automatic airport detection in remote sensing images using convolutional neural networks[J]. Remote Sensing, 10, 443(2018).

[19] 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), June 27-30, 2016, Las Vegas, NV, USA, 779-788(2016).

[20] Redmon J, Farhadi A. YOLOv3:an incremental improvement[EB/OL]. (2018-08-08)[2020-10-10]. https://arxiv.org/abs/1804.02767

[21] Li C Y, Yao J M, Lin Z X et al. Object detection method based on improved YOLO lightweight network[J]. Laser & Optoelectronics Progress, 57, 141003(2020).

[22] Guo J X, Liu L B, Xu F et al. Airport scene aircraft detection method based on YOLO v3[J]. Laser & Optoelectronics Progress, 56, 191003(2019).

[23] Zhang Y L, Yuan Y, Feng Y C et al. Hierarchical and robust convolutional neural network for very high-resolution remote sensing object detection[J]. IEEE Transactions on Geoscience and Remote Sensing, 57, 5535-5548(2019).

[24] Li K, Wan G, Cheng G et al. Object detection in optical remote sensing images: a survey and a new benchmark[J]. ISPRS Journal of Photogrammetry and Remote Sensing, 159, 296-307(2020).