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• W3127668714 abstract "SAR Ship Detection Dataset (SSDD) has been widely used by researchers because it can achieve a good tradeoff between model performance and time consumption of experiments. However, there is still a lack of performance benchmark for state-of-the-art methods on SSDD. On the one hand, this makes it difficult for researchers to grasp the performance of mainstream methods in general; on the other hand, research results of SAR ship detection based on deep learning cannot be compared horizontally in a unified experiment setup. To solve the lack of this solid work in the field of ship detection in SAR images based on deep learning, this paper benchmarks state-of-the-art detection methods on SSDD to provide an overview for future research work." @default.
• W3127668714 created "2021-02-15" @default.
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• W3127668714 date "2020-12-11" @default.
• W3127668714 modified "2023-09-27" @default.
• W3127668714 title "Ship Detection for SAR Imagery Based on Deep Learning: A Benchmark" @default.
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• W3127668714 doi "https://doi.org/10.1109/itaic49862.2020.9339055" @default.
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