{"title":"基于FFT的四层神经网络物种自动识别改进","authors":"Rong Sun, Y. Marye, Hua-An Zhao","doi":"10.1109/ISCIT.2013.6645912","DOIUrl":null,"url":null,"abstract":"In this paper, an automatic species identification system has been developed. Recoded data was segmented, processed, features taken out, and identified by an automatic operation. A feature quantity method based on FFT with derivative of frequency band power making use of 4-layer neural network is proposed. Comparison of the results with the 4-layer neural network has been performed on wild bird species identification based on sound data which has proved promising.","PeriodicalId":356009,"journal":{"name":"2013 13th International Symposium on Communications and Information Technologies (ISCIT)","volume":"20 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2013-10-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"8","resultStr":"{\"title\":\"FFT based automatic species identification improvement with 4-layer neural network\",\"authors\":\"Rong Sun, Y. Marye, Hua-An Zhao\",\"doi\":\"10.1109/ISCIT.2013.6645912\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In this paper, an automatic species identification system has been developed. Recoded data was segmented, processed, features taken out, and identified by an automatic operation. A feature quantity method based on FFT with derivative of frequency band power making use of 4-layer neural network is proposed. Comparison of the results with the 4-layer neural network has been performed on wild bird species identification based on sound data which has proved promising.\",\"PeriodicalId\":356009,\"journal\":{\"name\":\"2013 13th International Symposium on Communications and Information Technologies (ISCIT)\",\"volume\":\"20 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2013-10-24\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"8\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2013 13th International Symposium on Communications and Information Technologies (ISCIT)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ISCIT.2013.6645912\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2013 13th International Symposium on Communications and Information Technologies (ISCIT)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ISCIT.2013.6645912","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
FFT based automatic species identification improvement with 4-layer neural network
In this paper, an automatic species identification system has been developed. Recoded data was segmented, processed, features taken out, and identified by an automatic operation. A feature quantity method based on FFT with derivative of frequency band power making use of 4-layer neural network is proposed. Comparison of the results with the 4-layer neural network has been performed on wild bird species identification based on sound data which has proved promising.