{"title":"聚类分析的一种新方法","authors":"V. Sineglazov, O. Chumachenko, V. Gorbatiuk","doi":"10.1109/APUAVD.2017.8308815","DOIUrl":null,"url":null,"abstract":"A new clustering approach that is capable of finding clusters that are separated by some complex hypersurface is proposed. The approach can be useful for performing analysis of big amounts of unlabeled images that can be nowadays easily gathered, in particular by using unmanned aerial vehicle with mounted cameras. The approach is based on “softening” the initial clustering criterion and then using nonlinear optimization to find the optimal hypersurface that separates clusters.","PeriodicalId":163267,"journal":{"name":"2017 IEEE 4th International Conference Actual Problems of Unmanned Aerial Vehicles Developments (APUAVD)","volume":"263 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2017-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"A new approach in cluster analysis\",\"authors\":\"V. Sineglazov, O. Chumachenko, V. Gorbatiuk\",\"doi\":\"10.1109/APUAVD.2017.8308815\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"A new clustering approach that is capable of finding clusters that are separated by some complex hypersurface is proposed. The approach can be useful for performing analysis of big amounts of unlabeled images that can be nowadays easily gathered, in particular by using unmanned aerial vehicle with mounted cameras. The approach is based on “softening” the initial clustering criterion and then using nonlinear optimization to find the optimal hypersurface that separates clusters.\",\"PeriodicalId\":163267,\"journal\":{\"name\":\"2017 IEEE 4th International Conference Actual Problems of Unmanned Aerial Vehicles Developments (APUAVD)\",\"volume\":\"263 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2017-10-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2017 IEEE 4th International Conference Actual Problems of Unmanned Aerial Vehicles Developments (APUAVD)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/APUAVD.2017.8308815\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2017 IEEE 4th International Conference Actual Problems of Unmanned Aerial Vehicles Developments (APUAVD)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/APUAVD.2017.8308815","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
A new clustering approach that is capable of finding clusters that are separated by some complex hypersurface is proposed. The approach can be useful for performing analysis of big amounts of unlabeled images that can be nowadays easily gathered, in particular by using unmanned aerial vehicle with mounted cameras. The approach is based on “softening” the initial clustering criterion and then using nonlinear optimization to find the optimal hypersurface that separates clusters.
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
