Research Progress of Data Fusion Technology in Nondestructive Testing of Fruit Quality

被引：0
作者：
Mu, Yang [1 ]
Sun, An [1 ,2 ]
机构：
[1] School of Automation & Information Engineering, Sichuan University of Science & Engineering, Yibin
[2] Artificial Intelligence Key Laboratory of Sichuan Province, Yibin
来源：
Science and Technology of Food Industry | 2024年 / 45卷 / 22期
关键词：
data fusion; fruit; nondestructive examination; quality; spectrum;
D O I：
10.13386/j.issn1002-0306.2023100141
中图分类号：
学科分类号：
摘要：
In fruit quality non-destructive testing, information derived from a single data source often falls short in providing a comprehensive representation of the subject under scrutiny, resulting in lower accuracy in detection. Integrating multiple data sources through data fusion allows for a more comprehensive information set, enhancing the precision of the assessment to a certain extent. Currently, data fusion techniques are widely adopted in evaluating various aspects of fruits, holding promising prospects for further development. The article summarizes the methods, characteristics, and applications of data fusion in fruit assessment, and anticipates the future trends of this technology in the fruit detection domain by combining existing research findings. © The Author(s) 2024.
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页码：1 / 8
页数：7
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