{"title":"基于神经网络的人工视觉道路跟踪","authors":"M Mazo, F.J Rodriguez, E Santiso, M.A Sotelo","doi":"10.1016/0066-4138(94)90067-1","DOIUrl":null,"url":null,"abstract":"<div><p>It has been developed, built and tested an artificial vision based system to follow roads, which provides control signals, in a short time, by means of a joint of artificial neural nets. The image is segmented in “road” or “not road.” The obtained segmentation is the input for two neural nets, a classic architecture net (NN), and a TDNN (Time Delay Neural Network) one. The outputs provided by both nets, with a trajectory estimation, are introduced to a decision-making block, which selects the alternative containing less error. The classifier parameters are updated according to the current segmentation.</p></div>","PeriodicalId":100097,"journal":{"name":"Annual Review in Automatic Programming","volume":"19 ","pages":"Pages 209-214"},"PeriodicalIF":0.0000,"publicationDate":"1994-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1016/0066-4138(94)90067-1","citationCount":"4","resultStr":"{\"title\":\"Road following by artificial vision using neural network\",\"authors\":\"M Mazo, F.J Rodriguez, E Santiso, M.A Sotelo\",\"doi\":\"10.1016/0066-4138(94)90067-1\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><p>It has been developed, built and tested an artificial vision based system to follow roads, which provides control signals, in a short time, by means of a joint of artificial neural nets. The image is segmented in “road” or “not road.” The obtained segmentation is the input for two neural nets, a classic architecture net (NN), and a TDNN (Time Delay Neural Network) one. The outputs provided by both nets, with a trajectory estimation, are introduced to a decision-making block, which selects the alternative containing less error. The classifier parameters are updated according to the current segmentation.</p></div>\",\"PeriodicalId\":100097,\"journal\":{\"name\":\"Annual Review in Automatic Programming\",\"volume\":\"19 \",\"pages\":\"Pages 209-214\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"1994-01-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://sci-hub-pdf.com/10.1016/0066-4138(94)90067-1\",\"citationCount\":\"4\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Annual Review in Automatic Programming\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/0066413894900671\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Annual Review in Automatic Programming","FirstCategoryId":"1085","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/0066413894900671","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Road following by artificial vision using neural network
It has been developed, built and tested an artificial vision based system to follow roads, which provides control signals, in a short time, by means of a joint of artificial neural nets. The image is segmented in “road” or “not road.” The obtained segmentation is the input for two neural nets, a classic architecture net (NN), and a TDNN (Time Delay Neural Network) one. The outputs provided by both nets, with a trajectory estimation, are introduced to a decision-making block, which selects the alternative containing less error. The classifier parameters are updated according to the current segmentation.