Tensor-Based Classification Models for Hyperspectral Data Analysis
arXiv: Computer Vision and Pattern Recognition(2018)
摘要
In this paper, we present tensor-based linear and nonlinear models for hyperspectral data classification and analysis. By exploiting the principles of tensor algebra, we introduce new classification architectures, the weight parameters of which satisfy the rank-1 canonical decomposition property. Then, we propose learning algorithms to train both linear and nonlinear classifiers. The advantages of...
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关键词
Tensile stress,Hyperspectral imaging,Data models,Machine learning,Data analysis,Analytical models
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