{"title":"Buried Underwater Object Classification Using a Collaborative Multi-Aspect Classifier","authors":"J. Cartmill, M. Azimi-Sadjadi, N. Wachowski","doi":"10.1109/IJCNN.2007.4371232","DOIUrl":null,"url":null,"abstract":"In this paper, a new collaborative multi-aspect classification system (CMAC) is introduced. CMAC utilizes a group of collaborative decision-making agents capable of producing a high-confidence final decision based on features obtained over multiple aspects. This system is then applied to a buried underwater target classification problem. The results show that CMAC provides excellent multi-ping classification of mine-like objects while simultaneously reducing the number of false alarms compared to a multi-ping decision-level fusion classifier.","PeriodicalId":350091,"journal":{"name":"2007 International Joint Conference on Neural Networks","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2007-10-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"15","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2007 International Joint Conference on Neural Networks","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/IJCNN.2007.4371232","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 15
Abstract
In this paper, a new collaborative multi-aspect classification system (CMAC) is introduced. CMAC utilizes a group of collaborative decision-making agents capable of producing a high-confidence final decision based on features obtained over multiple aspects. This system is then applied to a buried underwater target classification problem. The results show that CMAC provides excellent multi-ping classification of mine-like objects while simultaneously reducing the number of false alarms compared to a multi-ping decision-level fusion classifier.