{"title":"A Multi Class Classification to Detect Original Form of Kaomoji using Neural Network","authors":"Noriyuki Okumura, Rei Okumura","doi":"10.5220/0008366203770382","DOIUrl":null,"url":null,"abstract":"In this paper, we propose a multi-class classification method for Kaomoji using feed forward neural network. Neural network has some units in each layer, but the suitable number of units is not clear. This research investigated the relation between the number of units and the accuracy of multi-class classification method.","PeriodicalId":133533,"journal":{"name":"International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management","volume":"34 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2019-09-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.5220/0008366203770382","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
In this paper, we propose a multi-class classification method for Kaomoji using feed forward neural network. Neural network has some units in each layer, but the suitable number of units is not clear. This research investigated the relation between the number of units and the accuracy of multi-class classification method.
京公网安备 11010802042870号
京ICP备2023020795号-1
分享
求助内容：
应助结果提醒方式：
扫码关注我们
