{"title":"聚焦cnn计算焦平面光流","authors":"M. Balsi","doi":"10.1109/CNNA.1998.685354","DOIUrl":null,"url":null,"abstract":"Optical flow computation is instrumental in robot guidance. Optoelectronic smart-pixel sensors for such computation may be realized on a single chip, by making use of a suitable cellular neural network architecture defined on a log-polar space-variant grid. Simulations confirm validity of the filtering system, and possible realizable structures are discussed.","PeriodicalId":171485,"journal":{"name":"1998 Fifth IEEE International Workshop on Cellular Neural Networks and their Applications. Proceedings (Cat. No.98TH8359)","volume":"25 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1998-04-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"8","resultStr":"{\"title\":\"Focal-plane optical flow computation by foveated CNNs\",\"authors\":\"M. Balsi\",\"doi\":\"10.1109/CNNA.1998.685354\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Optical flow computation is instrumental in robot guidance. Optoelectronic smart-pixel sensors for such computation may be realized on a single chip, by making use of a suitable cellular neural network architecture defined on a log-polar space-variant grid. Simulations confirm validity of the filtering system, and possible realizable structures are discussed.\",\"PeriodicalId\":171485,\"journal\":{\"name\":\"1998 Fifth IEEE International Workshop on Cellular Neural Networks and their Applications. Proceedings (Cat. No.98TH8359)\",\"volume\":\"25 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"1998-04-14\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"8\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"1998 Fifth IEEE International Workshop on Cellular Neural Networks and their Applications. Proceedings (Cat. No.98TH8359)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/CNNA.1998.685354\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"1998 Fifth IEEE International Workshop on Cellular Neural Networks and their Applications. Proceedings (Cat. No.98TH8359)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CNNA.1998.685354","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Focal-plane optical flow computation by foveated CNNs
Optical flow computation is instrumental in robot guidance. Optoelectronic smart-pixel sensors for such computation may be realized on a single chip, by making use of a suitable cellular neural network architecture defined on a log-polar space-variant grid. Simulations confirm validity of the filtering system, and possible realizable structures are discussed.