{"title":"复杂城市环境下一种高效的DAS信号识别方法","authors":"Xinyu Liu, Yufeng Wang, Liang Liu, Yunlin Tu, Yuwen Sun, Huijuan Wu, Yunjiang Rao","doi":"10.1364/ofs.2022.w4.21","DOIUrl":null,"url":null,"abstract":"An attention-based ResNet model is proposed for DAS signal recognition, by focusing on the key time-frequency information through feature attention of channel and local structure. The best recognition accuracy and computation efficiency are simultaneously achieved.","PeriodicalId":265406,"journal":{"name":"27th International Conference on Optical Fiber Sensors","volume":"19 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"An efficient DAS signal recognition method in complicated urban environments\",\"authors\":\"Xinyu Liu, Yufeng Wang, Liang Liu, Yunlin Tu, Yuwen Sun, Huijuan Wu, Yunjiang Rao\",\"doi\":\"10.1364/ofs.2022.w4.21\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"An attention-based ResNet model is proposed for DAS signal recognition, by focusing on the key time-frequency information through feature attention of channel and local structure. The best recognition accuracy and computation efficiency are simultaneously achieved.\",\"PeriodicalId\":265406,\"journal\":{\"name\":\"27th International Conference on Optical Fiber Sensors\",\"volume\":\"19 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"1900-01-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"27th International Conference on Optical Fiber Sensors\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1364/ofs.2022.w4.21\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"27th International Conference on Optical Fiber Sensors","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1364/ofs.2022.w4.21","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
An efficient DAS signal recognition method in complicated urban environments
An attention-based ResNet model is proposed for DAS signal recognition, by focusing on the key time-frequency information through feature attention of channel and local structure. The best recognition accuracy and computation efficiency are simultaneously achieved.
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