A method for comparative analysis of multidimensional data based on product characteristics

Xiangzhen Li; Peng Zhang; Kan Zhou; Xiaohang Wang; Hongcheng Yin; Xiaodan Xie; Xiao Wei

doi:10.1117/12.3023743

18 March 2024 A method for comparative analysis of multidimensional data based on product characteristics

Xiangzhen Li, Peng Zhang, Kan Zhou, Xiaohang Wang, Hongcheng Yin, Xiaodan Xie, Xiao Wei

Proceedings Volume 13104, Advanced Fiber Laser Conference (AFL2023); 1310463 (2024) https://doi.org/10.1117/12.3023743
Event: Advanced Fiber Laser Conference (AFL2023), 2023, Shenzhen, China

Abstract

Remote sensing technology plays a crucial role in today's world, providing a large amount of data for various fields. Different fields require detailed analysis of different types of product characteristics to meet different needs. Therefore, in-depth understanding of product characteristics is crucial to improve the efficiency of decision making and target management. The existing data comparative analysis methods of product characteristics often only carry out a single dimension comparison, which is not conducive to users to understand the target product characteristics. This paper designs a comparative analysis method of multi-dimensional data based on product characteristics. By obtaining different types of raw data of the target, feature extraction is carried out on each type of raw data respectively to obtain the corresponding feature data of each type, and different feature data are normalized. The normalized feature data is compared and displayed with the current type of known feature data of each known target in the database, and the comparison results of each dimension of the target are obtained.

(2024) Published by SPIE. Downloading of the abstract is permitted for personal use only.

Citation Download Citation

Xiangzhen Li, Peng Zhang, Kan Zhou, Xiaohang Wang, Hongcheng Yin, Xiaodan Xie, and Xiao Wei "A method for comparative analysis of multidimensional data based on product characteristics", Proc. SPIE 13104, Advanced Fiber Laser Conference (AFL2023), 1310463 (18 March 2024); https://doi.org/10.1117/12.3023743

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