Ship detection in SAR images based on an improved faster R-CNN

By Jianwei Li, Changwen Qu, Jiaqi Shao. 2017 SAR in Big Data Era: Models, Methods and Applications (BIGSARDATA), 2017

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Dense Attention Pyramid Networks for Multi-Scale Ship Detection in SAR Images (2019, methodology): “[38] put forward an improved faster R-CNN method and provided a data set called SAR ship detection data set (SSDD) to train and test a model.”
Automatic Ship Detection Based on RetinaNet Using Multi-Resolution Gaofen-3 Imagery (2019, methodology): “To co nter this, the f cal loss is proposed in Reference [21].”
Transformers in Remote Sensing: A Survey (2022, methodology): “CRTransSar [147] Detection SMCDD [147], SSDD [158] Accuracy,”
SAR Ship Detection Dataset (SSDD): Official Release and Comprehensive Data Analysis (2021, methodology): “, SAR Ship Detection Dataset (SSDD), publicly available to everyone at the conference of SAR in Big Data Era: Models, Methods and Applications (BIGSARDATA) in Beijing, China [28].”
HRSID: A High-Resolution SAR Images Dataset for Ship Detection and Instance Segmentation (2020, methodology): “In the SAR ship detection dataset (SSDD) [45], the SAR images have larger size but they need to be augmented before training and testing due to the limited data, and ship detection precision tested by the test set of SSDD are generally too high [30], [37].”
Deep Learning Meets SAR: Concepts, models, pitfalls, and perspectives (2020, background): “[104] fuses features of the last three convolution layers before feeding them to a region proposal network (RPN).”