{"title":"基于神经网络的纹理估计","authors":"B. Bourgeois, C. Walker","doi":"10.1109/ICNN.1991.163332","DOIUrl":null,"url":null,"abstract":"The authors investigate the use of neural networks for the direct estimation of image texture. Unlike previous approaches where networks are used to make decisions on feature vectors derived from traditional techniques, or where a network is trained to perform the function of a traditional technique, the proposed approach uses a network to directly model texture. The envisioned approaches to this method are described. Preliminary results of one-dimensional tests show that a neural network implementation is very adapt at recognizing irregular signals, even in the presence of added noise. This is intended to be applied in a Seafloor Acoustic Imagery via sidescan imagery.<<ETX>>","PeriodicalId":296300,"journal":{"name":"[1991 Proceedings] IEEE Conference on Neural Networks for Ocean Engineering","volume":"25 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1991-08-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Texture estimation with neural networks\",\"authors\":\"B. Bourgeois, C. Walker\",\"doi\":\"10.1109/ICNN.1991.163332\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The authors investigate the use of neural networks for the direct estimation of image texture. Unlike previous approaches where networks are used to make decisions on feature vectors derived from traditional techniques, or where a network is trained to perform the function of a traditional technique, the proposed approach uses a network to directly model texture. The envisioned approaches to this method are described. Preliminary results of one-dimensional tests show that a neural network implementation is very adapt at recognizing irregular signals, even in the presence of added noise. This is intended to be applied in a Seafloor Acoustic Imagery via sidescan imagery.<<ETX>>\",\"PeriodicalId\":296300,\"journal\":{\"name\":\"[1991 Proceedings] IEEE Conference on Neural Networks for Ocean Engineering\",\"volume\":\"25 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"1991-08-15\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"[1991 Proceedings] IEEE Conference on Neural Networks for Ocean Engineering\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICNN.1991.163332\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"[1991 Proceedings] IEEE Conference on Neural Networks for Ocean Engineering","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICNN.1991.163332","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
The authors investigate the use of neural networks for the direct estimation of image texture. Unlike previous approaches where networks are used to make decisions on feature vectors derived from traditional techniques, or where a network is trained to perform the function of a traditional technique, the proposed approach uses a network to directly model texture. The envisioned approaches to this method are described. Preliminary results of one-dimensional tests show that a neural network implementation is very adapt at recognizing irregular signals, even in the presence of added noise. This is intended to be applied in a Seafloor Acoustic Imagery via sidescan imagery.<>