{"title":"从已知类的形式中提取数据的系统","authors":"F. Cesarini, M. Gori, S. Marinai, G. Soda","doi":"10.1109/ICDAR.1995.602120","DOIUrl":null,"url":null,"abstract":"In this paper, we describe a flexible and efficient system for processing forms of a known class. The model is based on attributed relational graphs and the system performs form registration and location of information fields using algorithms based on the hypothesize-and-verify paradigm. A special emphasis has been placed at the low level, where an autoassociator-based connectionist model has exhibited successful results in finding the instruction fields in very noisy forms.","PeriodicalId":273519,"journal":{"name":"Proceedings of 3rd International Conference on Document Analysis and Recognition","volume":"27 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1995-08-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"13","resultStr":"{\"title\":\"A system for data extraction from forms of known class\",\"authors\":\"F. Cesarini, M. Gori, S. Marinai, G. Soda\",\"doi\":\"10.1109/ICDAR.1995.602120\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In this paper, we describe a flexible and efficient system for processing forms of a known class. The model is based on attributed relational graphs and the system performs form registration and location of information fields using algorithms based on the hypothesize-and-verify paradigm. A special emphasis has been placed at the low level, where an autoassociator-based connectionist model has exhibited successful results in finding the instruction fields in very noisy forms.\",\"PeriodicalId\":273519,\"journal\":{\"name\":\"Proceedings of 3rd International Conference on Document Analysis and Recognition\",\"volume\":\"27 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"1995-08-14\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"13\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings of 3rd International Conference on Document Analysis and Recognition\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICDAR.1995.602120\",\"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 of 3rd International Conference on Document Analysis and Recognition","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICDAR.1995.602120","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
A system for data extraction from forms of known class
In this paper, we describe a flexible and efficient system for processing forms of a known class. The model is based on attributed relational graphs and the system performs form registration and location of information fields using algorithms based on the hypothesize-and-verify paradigm. A special emphasis has been placed at the low level, where an autoassociator-based connectionist model has exhibited successful results in finding the instruction fields in very noisy forms.