Ship detection and identification in SDGSAT-1 glimmer images based on the glimmer YOLO model

References

• Cao, C., J. Wu, X. Zeng, Z. Feng, T. Wang, X. Yan, Z. Wu, Q. Wu, and Z. Huang. 2020. “Research on Airplane and Ship Detection of Aerial Remote Sensing Images Based on Convolutional Neural Network Images Based on Convolutional Neural Network.” Sensors (Basel) 20 (17), https://doi.org/10.3390/s20174696.
   Web of Science ®Google Scholar
• Chen, L., W. Shi, and D. Deng. 2021. “Improved YOLOv3 Based on Attention Mechanism for Fast and Accurate Ship Detection in Optical Remote Sensing Images.” Remote Sensing 13 (4): 660. https://doi.org/10.3390/rs13040660.
   Web of Science ®Google Scholar
• Dong, C., J. Liu, and F. Xu. 2018. “Ship Detection in Optical Remote Sensing Images Based on Saliency and a Rotation-Invariant Descriptor.” Remote Sensing 10 (3), https://doi.org/10.3390/rs10030400.
   Web of Science ®Google Scholar
• Elvidge, C. D., M. Zhizhin, K. Baugh, and F. Hsu. 2015. “Automatic Boat Identification System for VIIRS low Light Imaging Data.” Remote Sensing 7 (3): 3020–3036. https://doi.org/10.3390/rs70303020.
   Web of Science ®Google Scholar
• Girshick, R. 2015. “Fast R-CNN.” International Conference on Computer Vision IEEE Computer Society, 2015. https://doi.org/10.1109/ICCV.2015.169.
   Google Scholar
• Girshick, R., J. Donahue, T. Darrell, and J. Malik. 2014. “Rich Feature Hierarchies for Accurate Object Detection and Semantic Segmentation.” IEEE Conference on Computer Vision and Pattern Recognition. https://doi.org/10.1109/CVPR.2014.81.
   Google Scholar
• Han, X., L. Zhao, Y. Ning, and J. Hu. 2021. “ShipYolo: An Enhanced Model for Ship Detection.” Journal of Advanced Transportation 2021: 1–11. https://doi.org/10.1155/2021/1060182.
   Web of Science ®Google Scholar
• Hou, Q., D. Zhou, and J. Feng. 2021. “Coordinate Attention for Efficient Mobile Network design.” IEEE/CVF Conference on Computer Vision and Pattern Recognition 2021: 13708-13717. https://doi.org/10.1109/CVPR46437.2021.01350.
   Google Scholar
• Hu, J., L. Shen, and G. Sun. 2018. “Squeeze-and-Excitation Networks.” IEEE Conference on Computer Vision and Pattern Recognition 2018, pp. 7132-7141. https://doi.org/10.1109/CVPR.2018.00745.
   Google Scholar
• Huang, Z., X. Jiang, F. Wu, Y. Fu, Y. Zhang, T. Fu, and J. Pei. 2023. “An Improved Method for Ship Target Detection Based on YOLOv4.” Applied Sciences 13 (3): 1302. https://doi.org/10.3390/app13031302.
   Google Scholar
• Huang, L., B. Liu, B. Li, W. Guo, W. Yu, Z. Zhang, and W. Yu. 2017. “OpenSARShip: A Dataset Dedicated to Sentinel-1 Ship Interpretation.” IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing 11 (1): 195–208. https://doi.org/10.1109/JSTARS.2017.2755672.
   Web of Science ®Google Scholar
• Kumar, S. S., and M. U. Selvi. 2011. “Sea object detection using colour and texture classification.” Int. J. Computer Appl. in Engineering Sciences IJCAES 204 (1): 19–31. https://doi.org/10.1007/978-3-642-24043-0_3.
   Google Scholar
• Lin, T.-Y., P. Dollár, R. Girshick, K. He, B. Hariharan, and S. Belongie. 2017. “Feature pyramid networks for object detection.” IEEE Conference on Computer Vision and Pattern Recognition 2018, pp. 936-944. https://doi.org/10.1109/CVPR.2017.106.
   Google Scholar
• Lin, T.-Y., P. Goyal, R. Girshick, K. He, and P. Dollár. 2017. “Focal loss for dense object detection.” IEEE International Conference on Computer Vision 2017, pp. 2999-3007. https://doi.org/10.1109/ICCV.2017.324.
   Google Scholar
• Liu, W., D. Anguelov, D. Erhan, C. Szegedy, S. Reed, C.-Y. Fu, and A. C. Berg. 2016. “SSD: Single Shot Multibox Detector.” Computer Vision–ECCV 2016: 14th European Conference, Amsterdam, The Netherlands, October 11–14, 2016, Proceedings, Part I 14. https://doi.org/10.1007/978-3-319-46448-0_2.
   Google Scholar
• Liu, Z., J. Hu, L. Weng, and Y. Yang. 2017. “Rotated Region Based CNN for Ship Detection.” 2017 IEEE International Conference on Image Processing (ICIP) Beijing, People’s Republic of China, 2017, pp. 900-904. https://doi.org/10.1109/ICIP.2017.8296411.
   Google Scholar
• Liu, W., L. Ma, and H. Chen. 2018. “Arbitrary-oriented Ship Detection Framework in Optical Remote-Sensing Images.” IEEE Geoscience and Remote Sensing Letters 15 (6): 937–941. https://doi.org/10.1109/LGRS.2018.2813094.
   Web of Science ®Google Scholar
• Liu, Z., L. Yuan, L. Weng, and Y. Yang. 2017. “A High Resolution Optical Satellite Image Dataset for Ship Recognition and Some new Baselines.” International Conference on Pattern Recognition Applications and Methods 2: 324–331. https://doi.org/10.5220/0006120603240331.
   Google Scholar
• Nie, X., M. Duan, H. Ding, B. Hu, and E. K. Wong. 2020. “Attention Mask R-CNN for Ship Detection and Segmentation from Remote Sensing Images.” IEEE Access 8: 9325–9334. https://doi.org/10.1109/ACCESS.2020.2964540.
   Web of Science ®Google Scholar
• Nie, S., Z. Jiang, H. Zhang, B. Cai, and Y. Yao. 2018. “Inshore Ship Detection Based on Mask R-CNN.” IGARSS 2018-2018 IEEE International Geoscience and Remote Sensing Symposium 2018, 693–696. https://doi.org/10.1109/IGARSS.2018.8519123.
   Google Scholar
• Park, J., S. Woo, J.-Y. Lee, and I. S. Kweon. 2018. “Bam: Bottleneck Attention Module.” arXiv preprint 1807.06514. https://doi.org/10.48550/arXiv.1807.06514.
   Google Scholar
• Qi, S., J. Ma, J. Lin, Y. Li, and J. Tian. 2015. “Unsupervised Ship Detection Based on Saliency and S-HOG Descriptor from Optical Satellite Images.” IEEE Geoscience and Remote Sensing Letters 12 (7): 1451–1455. https://doi.org/10.1109/LGRS.2015.2408355.
   Web of Science ®Google Scholar
• Redmon, J., S. Divvala, R. Girshick, and A. Farhadi. 2016. “You Only Look Once: Unified, Real-Time Object Detection.” Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition 2016, 779–788. https://doi.org/10.1109/CVPR.2016.91.
   Google Scholar
• Redmon, J., and A. Farhadi. 2018. “Yolov3: An Incremental Improvement.” arXiv preprint 1804.02767. https://doi.org/10.48550/arXiv.1804.02767.
   Google Scholar
• Ren, S., K. He, R. Girshick, and J. Sun. 2015. “Faster r-cnn: Towards Real-Time Object Detection with Region Proposal Networks.” IEEE Transactions on Pattern Analysis and Machine Intelligence, https://doi.org/10.1109/TPAMI.2016.2577031.
   PubMed Web of Science ®Google Scholar
• Rezatofighi, H., N. Tsoi, J. Gwak, A. Sadeghian, I. Reid, and S. Savarese. 2019. “Generalized intersection over union: A metric and a loss for bounding box regression.” Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition 2019: 658-666. https://doi.org/10.1109/CVPR.2019.00075.
   Google Scholar
• Saitoh, S., A. Fukaya, K. Saitoh, B. Semedi, R. Mugo, S. Matsumura, and F. Takahashi. 2020. “Estimation of Number of Pacific Saury Fishing Vessels Using Night-Time Visible Images.” International Archives of the Photogrammetry Remote Sensing, and Spatial Information Science 2010.38 (Part 8): 1013–1016.
   Google Scholar
• Tan, M., R. Pang, and Q. V. Le. 2020. “Efficientdet: Scalable and Efficient Object Detection.” Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition 2020, 10781–10790.
   Google Scholar
• Waluda, C. M., C. Yamashiro, C. D. Elvidge, V. R. Hobson, and P. G. Rodhouse. 2004. “Quantifying Light-Fishing for Dosidicus Gigas in the Eastern Pacific Using Satellite Remote Sensing.” Remote Sensing of Environment 91 (2): 129–133. https://doi.org/10.1016/j.rse.2004.02.006.
   Web of Science ®Google Scholar
• Wang, Y., C. Wang, and H. Zhang. 2018. “Combining a Single Shot Multibox Detector with Transfer Learning for Ship Detection Using Sentinel-1 SAR Images.” Remote Sensing Letters 9 (8): 780–788. https://doi.org/10.1080/2150704X.2018.1475770.
   Web of Science ®Google Scholar
• Wang, Y., C. Wang, H. Zhang, Y. Dong, and S. Wei. 2019. “A SAR Dataset of Ship Detection for Deep Learning Under Complex Backgrounds.” Remote Sensing 11 (7): 765. https://doi.org/10.3390/rs11070765.
   Web of Science ®Google Scholar
• Wei, S., X. Zeng, Q. Qu, M. Wang, H. Su, and J. Shi. 2020. “HRSID: A High-Resolution SAR Images Dataset for Ship Detection and Instance Segmentation.” IEEE Access 8: 120234–54. https://doi.org/10.1109/ACCESS.2020.3005861.
   Web of Science ®Google Scholar
• Woo, S., J. Park, J.-Y. Lee, and I. S. Kweon. 2018. “Cbam: Convolutional block attention module.” Proceedings of the European Conference on Computer Vision (ECCV) 11211: 3–19. https://doi.org/10.1007/978-3-030-01234-2_1.
   Google Scholar
• Xu, X., X. Zhang, Z. Shao, J. Shi, S. Wei, T. Zhang, and T. Zeng. 2022a. “A Group-Wise Feature Enhancement-and-Fusion Network with Dual-Polarization Feature Enrichment for SAR Ship Detection.” Remote Sensing 14 (20): 5276. https://doi.org/10.3390/rs14205276.
   Web of Science ®Google Scholar
• Xu, X., X. Zhang, and T. Zhang. 2022b. “Lite-YOLOv5: A Lightweight Deep Learning Detector for On-Board Ship Detection in Large-Scene Sentinel-1 SAR Images.” Remote Sensing 14 (4): 1018. https://doi.org/10.3390/rs14041018.
   Web of Science ®Google Scholar
• Yang, G., B. Li, S. Ji, F. Gao, and Q. Xu. 2013. “Ship Detection from Optical Satellite Images Based on sea Surface Analysis.” IEEE Geoscience and Remote Sensing Letters 11 (3): 641–645. https://doi.org/10.1109/LGRS.2013.2273552.
   Web of Science ®Google Scholar
• Yang, X., H. Sun, K. Fu, J. Yang, X. Sun, M. Yan, and Z. Guo. 2018. “Automatic Ship Detection in Remote Sensing Images from Google Earth of Complex Scenes Based on Multiscale Rotation Dense Feature Pyramid Networks.” Remote Sensing 10 (1): 132. https://doi.org/10.3390/rs10010132.
   Web of Science ®Google Scholar
• Yu, J., Y. Jiang, Z. Wang, Z. Cao, and T. Huang. 2016. “Unitbox: An advanced object detection network.” Proceedings of the 24th ACM International Conference on Multimedia, https://doi.org/10.1145/2964284.2967274.
   Google Scholar
• Zhang, Z., W. Guo, S. Zhu, and W. Yu. 2018. “Toward Arbitrary-Oriented Ship Detection with Rotated Region Proposal and Discrimination Networks.” IEEE Geoscience and Remote Sensing Letters 15 (11): 1745–1749. https://doi.org/10.1109/LGRS.2018.2856921.
   Web of Science ®Google Scholar
• Zhang, Y.-F., W. Ren, Z. Zhang, Z. Jia, L. Wang, and T. Tan. 2022. “Focal and Efficient IOU Loss for Accurate Bounding box Regression.” Neurocomputing 506: 146–157. https://doi.org/10.1016/j.neucom.2022.07.042.
   Web of Science ®Google Scholar
• Zhang, P., G. Xie, and J. Zhang. 2022. “Gaussian Function Fusing Fully Convolutional Network and Region Proposal-Based Network for Ship Target Detection in SAR Images.” International Journal of Antennas and Propagation 2022), https://doi.org/10.1155/2022/3063965.
   Web of Science ®Google Scholar
• Zhang, R., J. Yao, K. Zhang, C. Feng, and J. Zhang. 2016. “S-CNN-based Ship Detection from High-Resolution Remote Sensing Images.” The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, https://doi.org/10.5194/isprs-archives-XLI-B7-423-2016.
   Google Scholar
• Zhang, T., X. Zhang, J. Li, X. Xu, B. Wang, X. Zhan, Y. Xu, X. Ke, T. Zeng, and H. Su. 2021. “SAR Ship Detection Dataset (SSDD): Official Release and Comprehensive Data Analysis.” Remote Sensing 13 (18): 3690. https://doi.org/10.3390/rs13183690.
   Web of Science ®Google Scholar
• Zhang, T., X. Zhang, J. Shi, and S. Wei. 2019. “Depthwise Separable Convolution Neural Network for High-Speed SAR Ship Detection.” Remote Sensing 11 (21): 2483. https://doi.org/10.3390/rs11212483.
   Web of Science ®Google Scholar
• Zhang, Z., L. Zhang, Y. Wang, P. Feng, and R. He. 2021. “ShipRSImageNet: A Large-Scale Fine-Grained Dataset for Ship Detection in High-Resolution Optical Remote Sensing Images.” IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing 14: 8458–8472. https://doi.org/10.1109/JSTARS.2021.3104230.
   Web of Science ®Google Scholar
• Zheng, Z., P. Wang, D. Ren, W. Liu, R. Ye, Q. Hu, and W. Zuo. 2021. “Enhancing Geometric Factors in Model Learning and Inference for Object Detection and Instance Segmentation.” IEEE Transactions on Cybernetics 52 (8): 8574–8586. https://doi.org/10.1109/TCYB.2021.3095305.
   Web of Science ®Google Scholar
• Zhong, L., X. Liu, P. Yang, and R. Lin. 2020. “Explore the Application of High-Resolution Nighttime Light Remote Sensing Images in Nighttime Marine Ship Detection: A Case Study of LJ1-01 Data.” Open Geosciences 12 (1): 1169–1184. https://doi.org/10.1515/geo-2020-0180.
   Web of Science ®Google Scholar
• Zou, Z., and Z. Shi. 2016. “Ship Detection in Spaceborne Optical Image with SVD Networks.” IEEE Transactions on Geoscience and Remote Sensing 54 (10): 5832–5845. https://doi.org/10.1109/TGRS.2016.2572736.
   Web of Science ®Google Scholar