{"title":"基于人工智能的烟叶分类研究综述","authors":"Guangcai Li, Huanju Zhen, Deji Wang, Cuilan Wang","doi":"10.1109/ICCST50977.2020.00086","DOIUrl":null,"url":null,"abstract":"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.","PeriodicalId":189809,"journal":{"name":"2020 International Conference on Culture-oriented Science & Technology (ICCST)","volume":"182 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2020-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":"{\"title\":\"Review of tobacco leaf classification research based on artificial intelligence\",\"authors\":\"Guangcai Li, Huanju Zhen, Deji Wang, Cuilan Wang\",\"doi\":\"10.1109/ICCST50977.2020.00086\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"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.\",\"PeriodicalId\":189809,\"journal\":{\"name\":\"2020 International Conference on Culture-oriented Science & Technology (ICCST)\",\"volume\":\"182 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2020-10-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2020 International Conference on Culture-oriented Science & Technology (ICCST)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICCST50977.2020.00086\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2020 International Conference on Culture-oriented Science & Technology (ICCST)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICCST50977.2020.00086","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
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.