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Image Classification Based on Weighted Topics

机译:基于加权主题的图像分类

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摘要

Probabilistic topic models have been applied to image classification and permit to obtain good results. However, these methods assumed that all topics have an equal contribution to classification. We propose a weight learning approach for identifying the discriminative power of each topic. The weights are employed to define the similarity distance for the subsequent classifier, e.g. KNN or SVM. Experiments show that the proposed method performs effectively for image classification.
机译:概率主题模型已应用于图像分类,并允许获得良好的结果。但是,这些方法假定所有主题对分类都具有同等的贡献。我们提出一种权重学习方法,以识别每个主题的区分能力。权重用于定义后续分类器(例如,分类器)的相似距离。 KNN或SVM。实验表明,该方法能有效地进行图像分类。

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