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Randomized tensor-based algorithm for image classification

机译:基于随机张量的图像分类算法

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We present a method for the image classification problem. First, the set of images is organized in a tensor format. Then, we define several classes in terms of subtensors of the same type of images. The method relies on the tensor dimensionality reduction algorithm to create the basis of the subtensor. Our algorithm was tested on the AT&T database of faces. From our experiments, the algorithm successfully classifies unknown images from the measured residual.
机译:我们提出一种图像分类问题的方法。首先,以张量格式组织图像集。然后,我们根据相同类型图像的张量定义几个类。该方法依靠张量降维算法来创建次张量的基础。我们的算法已在AT&T人脸数据库上进行了测试。从我们的实验中,该算法成功地根据测量的残差对未知图像进行了分类。

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