基于改进Mobilenet-YOLOv3的轻量级水下生物检测算法
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郝琨,王阔,王贝贝
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Lightweight underwater biological detection algorithm based on improved Mobilenet-YOLOv3
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Kun HAO,Kuo WANG,Bei-bei WANG
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| 表 4 CBAM对模型大小及检测精度的影响 |
| Tab.4 Effect of CBAM on model size and detection accuracy |
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| 网络模型 | Para/MB | M/MB | R/% | AP/% | AP50/% | AP75/% | T/ms | | Mobilenet-YOLOv3 Prune90% | 2.22 | 9.08 | 89.3 | 85.8 | 86.8 | 85.5 | 4.5 | | + CBAM替换SE | 1.14 | 4.84 | 89.6 | 86.0 | 87.1 | 85.9 | 4.9 | | + 在预测层加入CBAM | 1.14 | 4.86 | 89.7 | 87.0 | 88.0 | 87.0 | 5.1 | | Mobilenet-YOLOv3 Prune90% (调整降维比例) | 0.80 | 3.46 | 88.2 | 85.2 | 85.2 | 84.3 | 4.3 |
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