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中国精品科技期刊2020
牟阳,孙安. 数据融合技术在水果品质无损检测中的研究进展[J]. 食品工业科技,2024,45(22):1−8. doi: 10.13386/j.issn1002-0306.2023100141.
引用本文: 牟阳,孙安. 数据融合技术在水果品质无损检测中的研究进展[J]. 食品工业科技,2024,45(22):1−8. doi: 10.13386/j.issn1002-0306.2023100141.
MU Yang, SUN An. Research Progress of Data Fusion Technology in Nondestructive Testing of Fruit Quality[J]. Science and Technology of Food Industry, 2024, 45(22): 1−8. (in Chinese with English abstract). doi: 10.13386/j.issn1002-0306.2023100141.
Citation: MU Yang, SUN An. Research Progress of Data Fusion Technology in Nondestructive Testing of Fruit Quality[J]. Science and Technology of Food Industry, 2024, 45(22): 1−8. (in Chinese with English abstract). doi: 10.13386/j.issn1002-0306.2023100141.

数据融合技术在水果品质无损检测中的研究进展

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

  • 摘要: 在水果品质无损检测中,单一数据源得到的信息往往不够全面,无法充分表征被测对象的相关信息,导致检测精度较低。通过数据融合的方式将多个数据源协同互补,可获得更丰富的信息,在一定程度上改善检测结果的精度。目前数据融合技术已广泛应用于水果各方面指标的检测中,具有良好的发展前景。文章总结了数据融合的方式、特点及其在水果检测领域的应用情况,并结合当前的研究现状对数据融合技术在水果检测中的发展趋势进行展望。

     

    Abstract: 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 have been 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.

     

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