高维上下文注意和双感受野增强的SAR船舶检测
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郭伟, 李煜, 金海波
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Detecting ships from SAR images based on high-dimensional contextual attention and dual receptive field enhancement
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GUO Wei, LI Yu, JIN Haibo
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表1 E-HRSID和SSDD数据集对比实验结果
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Tab.1 Comparison experiment results of E-HRSID and SSDD datasets
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模型 | E-HRSID | SSDD | P/% | R/% | mAP/% | F1 | P/% | R/% | mAP/% | F1 | CenterNet | 96.63 | 60.95 | 76.77 | 0.75 | 97.46 | 75.42 | 89.04 | 0.83 | Efficientdet | 97.29 | 22.36 | 34.73 | 0.36 | 95.77 | 25.09 | 73.83 | 0.40 | Faster R-CNN | 34.3 | 35.71 | 26.95 | 0.35 | 73.50 | 68.07 | 88.12 | 0.71 | RetinaNet | 93.31 | 27.65 | 34.35 | 0.43 | 86.81 | 63.14 | 80.86 | 0.73 | SSD | 88.79 | 16.34 | 40.64 | 0.28 | 95.80 | 42.07 | 89.58 | 0.58 | YOLOv7 | 88.16 | 78.16 | 86.80 | 0.83 | 90.80 | 78.00 | 87.81 | 0.84 | YOLOv8 | 89.53 | 83.27 | 90.47 | 0.86 | 95.40 | 91.80 | 97.10 | 0.94 | YOLO-HD | 90.65 | 84.36 | 91.36 | 0.87 | 95.25 | 95.55 | 97.64 | 0.95 |
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