基于人工智能的烟叶分类研究综述

Guangcai Li, Huanju Zhen, Deji Wang, Cuilan Wang
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引用次数: 2

摘要

为完成国产局发布的烟叶智能分类研究,提高原料保障水平,研究国内烟叶分级技术发展趋势,以国内烟叶研究成果为数据源,采用关联分析、聚类分析、NLP分析等作为分析工具。对1979 - 2019年烟叶分级数据进行分析,分析烟叶分级的主要研究机构、核心作者和研究热点。最后,提出了我国烟草分级研究的现状和存在的问题,以及烟草分级研究的规律和趋势。特别指出“高光谱+深度学习+专家系统”将成为研究热点,其中深度学习是研究重点。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Review of tobacco leaf classification research based on artificial intelligence
In order to complete the research on intelligent classification of tobacco leaves issued by the National Bureau, improve the level of raw material assurance, and study the development trend of domestic tobacco grading technology, using domestic tobacco research results as data sources, association analysis, cluster analysis, NLP analysis, etc. are used as analysis tools. The grading data from 1979 to 2019 were analyzed, and the main research institutions, core authors, and research hotspots of tobacco grading were analyzed. Finally, the status and existing problems of tobacco grading research, as well as the rules and trends of tobacco grading research are given. In particular, it is pointed out that "hyperspectral + deep learning + expert system" will become a research hotspot, among which deep learning is a research Focus.
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