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首页> 外文会议>International conference on graphic and image processing >Vehicle Logo Recognition Using Multi-level Fusion Model
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Vehicle Logo Recognition Using Multi-level Fusion Model

机译：基于多级融合模型的车辆标志识别

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Vehicle logo recognition plays an important role in manufacturer identification and vehicle recognition. This paper proposes a new vehicle logo recognition algorithm. It has a hierarchical framework, which consists of two fusion levels. At the first level, a feature fusion model is employed to map the original features to a higher dimension feature space. In this space, the vehicle logos become more recognizable. At the second level, a weighted voting strategy is proposed to promote the accuracy and the robustness of the recognition results. To evaluate the performance of the proposed algorithm, extensive experiments are performed, which demonstrate that the proposed algorithm can achieve high recognition accuracy and work robustly.
机译：车辆徽标识别在制造商识别和车辆识别中起着重要作用。提出了一种新的车辆标志识别算法。它具有一个层次结构的框架，该框架包含两个融合级别。在第一级，采用特征融合模型将原始特征映射到更高维度的特征空间。在这个空间中，车辆徽标变得更加容易辨认。在第二级，提出了一种加权投票策略，以提高识别结果的准确性和鲁棒性。为了评估所提算法的性能，进行了广泛的实验，结果表明所提算法可以达到较高的识别精度并且鲁棒性强。

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