Ship Remote Sensing Target Recognition Based on YOLOV5
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Publisher
Springer Nature Switzerland
Link
https://link.springer.com/content/pdf/10.1007/978-3-031-44947-5_44
Reference13 articles.
1. Yi, L., Shoushi, X.: A method for ship target recognition in remote sensing images based on support vector machines. Comput. Simul. 2006(06), 180–183 (2006)
2. Xia, Y., Wan, S., Yue, L.: A novel algorithm for ship detection based on dynamic fusion model of multi-feature and support vector machine. In: Proceedings of the 2011 Sixth International Conference on Image and Graphics, Hefei, China, pp. 521–526 (2011). https://doi.org/10.1109/ICIG.2011.147
3. Zou, Z., Shi, Z.: Ship detection in spaceborne optical image with SVD networks. IEEE Trans. Geosci. Remote Sens. 54(10), 5832–5845 (2016). https://doi.org/10.1109/TGRS.2016.2572736
4. Nie, S., Jiang, Z., Zhang, H., Cai, B., Yao, Y.: Inshore ship detection based on mask R-CNN. In: IGARSS 2018—2018 IEEE International Geoscience and Remote Sensing Symposium, Valencia, Spain, pp. 693–696 (2018). https://doi.org/10.1109/IGARSS.2018.8519123
5. Wei, S., Chen, H., Zhu, X., Zhang, H.: Ship detection in remote sensing image based on faster R-CNN with dilated convolution. In: Proceedings of the 2020 39th Chinese control conference (CCC), Shenyang, China, pp. 7148–7153 (2020). https://doi.org/10.23919/CCC50068.2020.9189467
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