期刊论文

Qing, Xiangdong;Zhang, J

英文

Talanta

0039-9140

2024

273

125845

10.1016/j.talanta.2024.125845

CRediT authorship contribution statement Xiangdong Qing: Writing – original draft, Methodology, Investigation, Formal analysis. Guiying Lu: Writing – review & editing, Investigation, Formal analysis, Data curation. Xiaohua Zhang: Writing – review & editing, Software, Resources. Qingling Chen: Validation, Resources, Data curation. Xiaohong Zhou: Investigation, acquisition. Wei He: Validation, Data curation. Ling Xu: Resources, Project administration. Jin Zhang: Writing – review & editing, Investigation, Conceptualization.

本校为第一且通讯机构

Classifying big data in hyperspectral imaging (HSI) can be challenging when minor (low-concentrated) compounds are present in actual samples, as for chemical additives and adulterants in food matrix. Herein, we propose a new strategy to classify HSI data for the identification of adulterants in food material for the first time. This strategy is based on the selection of essential spectral pixels of full HSI data followed by the feature space construction using uniform manifold approximation and projection as well as the data clustering utilizing hierarchical clustering analysis on the reduced ...