联合正交特征融合与大核可分离注意力的道路分割算法
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汤毅杰,钟铭恩,袁彬淦,范康,谭佳威,林志强
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Road segmentation algorithm based on joint orthogonal feature fusion and large kernel separable attention
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Yijie TANG,Mingen ZHONG,Bingan YUAN,Kang FAN,Jiawei TAN,Zhiqiang LIN
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| 表 3 不同剪枝方法性能对比结果 |
| Tab.3 Performance comparison of different pruning methods |
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| 方法 | Massachusetts数据集 | | DeepGlobe数据集 | 参数量/106 | FLOPs/109 | | P/% | R/% | IoU/% | APLS/% | | P/% | R/% | IoU/% | APLS/% | | 未剪枝 | 78.65 | 79.98 | 65.12 | 75.36 | | 80.21 | 81.98 | 68.41 | 75.93 | 37.3 | 29.2 | | L1[29] | 74.62 | 75.88 | 61.47 | 71.83 | | 76.35 | 77.68 | 64.58 | 72.78 | 22.5 | 14.9 | | Group norm[30] | 75.58 | 76.93 | 62.38 | 72.08 | | 77.63 | 78.74 | 65.47 | 73.51 | 22.8 | 15.3 | | Group hessian[31] | 74.96 | 76.39 | 61.95 | 71.92 | | 76.53 | 78.31 | 64.89 | 72.87 | 22.7 | 15.4 | | Group taylor[32] | 74.35 | 75.43 | 61.18 | 71.69 | | 76.02 | 77.33 | 64.08 | 72.28 | 22.8 | 15.1 | | LAMP | 78.12 | 79.63 | 64.85 | 74.95 | | 79.78 | 81.63 | 67.88 | 75.53 | 22.5 | 14.8 |
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