{"title":"基于机器学习的水下目标检测","authors":"Wen Zhang, Yanqun Wu, Yonggang Lin, Lina Ma, Kaifeng Han, Yu Chen, Chen Liu","doi":"10.1109/ICICSP50920.2020.9232081","DOIUrl":null,"url":null,"abstract":"Underwater target detection is an important part of acoustic signal processing. It is mainly composed of bad channel detection, beamforming, classification, tracking and localization. In this paper, the possibility of realizing bad channel detection, classification, tracking and localization based on Machine Learning or Deep Learning was explored. And they were all implemented separately and successfully using Machine Learning or Deep Learning.","PeriodicalId":117760,"journal":{"name":"2020 IEEE 3rd International Conference on Information Communication and Signal Processing (ICICSP)","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2020-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"5","resultStr":"{\"title\":\"Underwater Target Detection Based on Machine Learning\",\"authors\":\"Wen Zhang, Yanqun Wu, Yonggang Lin, Lina Ma, Kaifeng Han, Yu Chen, Chen Liu\",\"doi\":\"10.1109/ICICSP50920.2020.9232081\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Underwater target detection is an important part of acoustic signal processing. It is mainly composed of bad channel detection, beamforming, classification, tracking and localization. In this paper, the possibility of realizing bad channel detection, classification, tracking and localization based on Machine Learning or Deep Learning was explored. And they were all implemented separately and successfully using Machine Learning or Deep Learning.\",\"PeriodicalId\":117760,\"journal\":{\"name\":\"2020 IEEE 3rd International Conference on Information Communication and Signal Processing (ICICSP)\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2020-09-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"5\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2020 IEEE 3rd International Conference on Information Communication and Signal Processing (ICICSP)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICICSP50920.2020.9232081\",\"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 IEEE 3rd International Conference on Information Communication and Signal Processing (ICICSP)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICICSP50920.2020.9232081","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Underwater Target Detection Based on Machine Learning
Underwater target detection is an important part of acoustic signal processing. It is mainly composed of bad channel detection, beamforming, classification, tracking and localization. In this paper, the possibility of realizing bad channel detection, classification, tracking and localization based on Machine Learning or Deep Learning was explored. And they were all implemented separately and successfully using Machine Learning or Deep Learning.
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