{"title":"基于改进AdaBoost算法的图像检测研究","authors":"Peng Wu, Shenming Qu","doi":"10.1109/MVHI.2010.104","DOIUrl":null,"url":null,"abstract":"In order to prevent more effectively the occurrence of the distortion of target weights’ distribution and further reduce system errors, a comprehensive improvement has been conducted on the algorithm’s weight updating and weight normalization to avoid the defects of the traditional AdaBoost image detection algorithm. It is proved that the improved algorithm is more effective.","PeriodicalId":34860,"journal":{"name":"HumanMachine Communication Journal","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2010-04-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Research of Image Detection Based on Improved AdaBoost Algorithm\",\"authors\":\"Peng Wu, Shenming Qu\",\"doi\":\"10.1109/MVHI.2010.104\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In order to prevent more effectively the occurrence of the distortion of target weights’ distribution and further reduce system errors, a comprehensive improvement has been conducted on the algorithm’s weight updating and weight normalization to avoid the defects of the traditional AdaBoost image detection algorithm. It is proved that the improved algorithm is more effective.\",\"PeriodicalId\":34860,\"journal\":{\"name\":\"HumanMachine Communication Journal\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2010-04-24\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"HumanMachine Communication Journal\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/MVHI.2010.104\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"Social Sciences\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"HumanMachine Communication Journal","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/MVHI.2010.104","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"Social Sciences","Score":null,"Total":0}
Research of Image Detection Based on Improved AdaBoost Algorithm
In order to prevent more effectively the occurrence of the distortion of target weights’ distribution and further reduce system errors, a comprehensive improvement has been conducted on the algorithm’s weight updating and weight normalization to avoid the defects of the traditional AdaBoost image detection algorithm. It is proved that the improved algorithm is more effective.
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