{"title":"用于图像预处理的what-and-where神经网络","authors":"G. Carpenter, S. Grossberg, G. Lesher","doi":"10.1109/IJCNN.1992.227157","DOIUrl":null,"url":null,"abstract":"A feedforward neural networks for invariant image preprocessing is proposed that represents the position, orientation, and size of an image figure (where it is) in a multiplexed spatial map. This map is used to generate an invariant representation of the figure that is insensitive to position, orientation, and size for purposes of pattern recognition (what it is). Image recognition is based upon the output from the what channel. A multiscale array of oriented filters, followed by competition between orientations and scales, is used to define the where filter.<<ETX>>","PeriodicalId":286849,"journal":{"name":"[Proceedings 1992] IJCNN International Joint Conference on Neural Networks","volume":"54 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1992-06-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"18","resultStr":"{\"title\":\"A what-and-where neural network for invariant image preprocessing\",\"authors\":\"G. Carpenter, S. Grossberg, G. Lesher\",\"doi\":\"10.1109/IJCNN.1992.227157\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"A feedforward neural networks for invariant image preprocessing is proposed that represents the position, orientation, and size of an image figure (where it is) in a multiplexed spatial map. This map is used to generate an invariant representation of the figure that is insensitive to position, orientation, and size for purposes of pattern recognition (what it is). Image recognition is based upon the output from the what channel. A multiscale array of oriented filters, followed by competition between orientations and scales, is used to define the where filter.<<ETX>>\",\"PeriodicalId\":286849,\"journal\":{\"name\":\"[Proceedings 1992] IJCNN International Joint Conference on Neural Networks\",\"volume\":\"54 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"1992-06-07\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"18\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"[Proceedings 1992] IJCNN International Joint Conference on Neural Networks\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/IJCNN.1992.227157\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"[Proceedings 1992] IJCNN International Joint Conference on Neural Networks","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/IJCNN.1992.227157","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
A what-and-where neural network for invariant image preprocessing
A feedforward neural networks for invariant image preprocessing is proposed that represents the position, orientation, and size of an image figure (where it is) in a multiplexed spatial map. This map is used to generate an invariant representation of the figure that is insensitive to position, orientation, and size for purposes of pattern recognition (what it is). Image recognition is based upon the output from the what channel. A multiscale array of oriented filters, followed by competition between orientations and scales, is used to define the where filter.<>