Mohamed El-Sharkawy, Anurag Bansal, Mostafa Analoui, Harry Gundrum
{"title":"快速修剪龋齿分类器","authors":"Mohamed El-Sharkawy, Anurag Bansal, Mostafa Analoui, Harry Gundrum","doi":"10.1109/MWSCAS.1995.510279","DOIUrl":null,"url":null,"abstract":"In this paper, we propose two new algorithms that use the pruned fast Fourier transform to generate the input to a backpropagation neural network of a dental caries classifier. The proposed systems eliminate the generation of digital sampling detector lookup table and the extraction of spectral feature vectors using the digital sampling detector. The proposed algorithms greatly reduced the number of complex multiplications and improved the speed-up factors.","PeriodicalId":165081,"journal":{"name":"38th Midwest Symposium on Circuits and Systems. Proceedings","volume":"9 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1995-08-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Fast pruned dental caries classifiers\",\"authors\":\"Mohamed El-Sharkawy, Anurag Bansal, Mostafa Analoui, Harry Gundrum\",\"doi\":\"10.1109/MWSCAS.1995.510279\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In this paper, we propose two new algorithms that use the pruned fast Fourier transform to generate the input to a backpropagation neural network of a dental caries classifier. The proposed systems eliminate the generation of digital sampling detector lookup table and the extraction of spectral feature vectors using the digital sampling detector. The proposed algorithms greatly reduced the number of complex multiplications and improved the speed-up factors.\",\"PeriodicalId\":165081,\"journal\":{\"name\":\"38th Midwest Symposium on Circuits and Systems. Proceedings\",\"volume\":\"9 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"1995-08-13\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"38th Midwest Symposium on Circuits and Systems. Proceedings\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/MWSCAS.1995.510279\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"38th Midwest Symposium on Circuits and Systems. Proceedings","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/MWSCAS.1995.510279","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
In this paper, we propose two new algorithms that use the pruned fast Fourier transform to generate the input to a backpropagation neural network of a dental caries classifier. The proposed systems eliminate the generation of digital sampling detector lookup table and the extraction of spectral feature vectors using the digital sampling detector. The proposed algorithms greatly reduced the number of complex multiplications and improved the speed-up factors.