{"title":"一种用于消失点计算的VLSI卷积神经网络结构","authors":"M. Villemur, M. Di Federico, P. Julián","doi":"10.1109/EAMTA.2015.7237379","DOIUrl":null,"url":null,"abstract":"This paper presents a VLSI Convolutional Neural Network with special features to implement the Vanishing Point algorithm. The architecture is based on a multi-scale array, with one column processor that implements a neural network with local connectivity, a row processor of SIMD elements that can implement generic convolution and a voting mechanism, which is used by the Vanishing Point algorithm. In addition, a 32-bit 7 pipeline-stage has been designed to sequence all the operations. Simulations of the architecture described in a Hardware description language are shown.","PeriodicalId":101792,"journal":{"name":"2015 Argentine School of Micro-Nanoelectronics, Technology and Applications (EAMTA)","volume":"102 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2015-07-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"A VLSI convolutional neural network architecture for vanishing point computation\",\"authors\":\"M. Villemur, M. Di Federico, P. Julián\",\"doi\":\"10.1109/EAMTA.2015.7237379\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This paper presents a VLSI Convolutional Neural Network with special features to implement the Vanishing Point algorithm. The architecture is based on a multi-scale array, with one column processor that implements a neural network with local connectivity, a row processor of SIMD elements that can implement generic convolution and a voting mechanism, which is used by the Vanishing Point algorithm. In addition, a 32-bit 7 pipeline-stage has been designed to sequence all the operations. Simulations of the architecture described in a Hardware description language are shown.\",\"PeriodicalId\":101792,\"journal\":{\"name\":\"2015 Argentine School of Micro-Nanoelectronics, Technology and Applications (EAMTA)\",\"volume\":\"102 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2015-07-30\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2015 Argentine School of Micro-Nanoelectronics, Technology and Applications (EAMTA)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/EAMTA.2015.7237379\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2015 Argentine School of Micro-Nanoelectronics, Technology and Applications (EAMTA)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/EAMTA.2015.7237379","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
A VLSI convolutional neural network architecture for vanishing point computation
This paper presents a VLSI Convolutional Neural Network with special features to implement the Vanishing Point algorithm. The architecture is based on a multi-scale array, with one column processor that implements a neural network with local connectivity, a row processor of SIMD elements that can implement generic convolution and a voting mechanism, which is used by the Vanishing Point algorithm. In addition, a 32-bit 7 pipeline-stage has been designed to sequence all the operations. Simulations of the architecture described in a Hardware description language are shown.