Stable third-order tensor representation for colour image classification

D. Tao, S. Maybank, Weiming Hu, Xuelong Li
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引用次数: 7

Abstract

General tensors can represent colour images more naturally than conventional features; however, the general tensors' stability properties are not reported and remain to be a key problem. In this paper, we use the tensor minimax probability (TMPM) to prove that the tensor representation is stable. The proof is based on the random subspace method through a large number of experiments.
彩色图像分类的稳定三阶张量表示
一般张量可以比常规特征更自然地表示彩色图像;然而,一般张量的稳定性尚未被报道,仍然是一个关键问题。本文利用张量极大极小概率(TMPM)证明了该张量表示是稳定的。通过大量的实验,证明了基于随机子空间的方法。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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