基于高维特征表示的交通场景识别
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刘文华,李浥东,王涛,邬俊,金一
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Transportation scene recognition based on high level feature representation
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Wenhua LIU,Yidong LI,Tao WANG,Jun WU,Yi JIN
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表3 不同网络结构的识别性能对比
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| 网络结构 | 识别准确率 | | Sport | Indoor | Outdoor | 15 Scene | | CaffeNet | 94.91% | 60.05% | 94.54% | 88.62% | | AlexNet | 94.06% | 58.15% | 93.42% | 86.84% | | VGGNet16 | 96.21% | 64.13% | 92.30% | 91.23% | | Places-CNN | 94.12% | 68.24% | 95.23% | 90.19% | | Softattribute | 93.87% | 66.43% | 98.71% | 88.48% | | AttributesFinetune | 96.23% | 68.32% | 98.83% | 91.92% |
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