{"title":"泛在文档捕获与深度学习","authors":"T. Naz, A. A. Khan, F. Shafait","doi":"10.1109/DICTA.2017.8227501","DOIUrl":null,"url":null,"abstract":"Digital and paper based documents co-exist in our daily lives. Seamless integration of information from both sources is crucial for efficient knowledge management. This paper address the algorithm that can handle the detection of document so that it can be captured easily to convert it into a digital form for automatic integration of relevant information in electronic work flows. It uses the deep learning technique to provide a solution which is more generalized and flexible than other available solutions.","PeriodicalId":194175,"journal":{"name":"2017 International Conference on Digital Image Computing: Techniques and Applications (DICTA)","volume":"34 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2017-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Ubiquitous Document Capturing with Deep Learning\",\"authors\":\"T. Naz, A. A. Khan, F. Shafait\",\"doi\":\"10.1109/DICTA.2017.8227501\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Digital and paper based documents co-exist in our daily lives. Seamless integration of information from both sources is crucial for efficient knowledge management. This paper address the algorithm that can handle the detection of document so that it can be captured easily to convert it into a digital form for automatic integration of relevant information in electronic work flows. It uses the deep learning technique to provide a solution which is more generalized and flexible than other available solutions.\",\"PeriodicalId\":194175,\"journal\":{\"name\":\"2017 International Conference on Digital Image Computing: Techniques and Applications (DICTA)\",\"volume\":\"34 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2017-11-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2017 International Conference on Digital Image Computing: Techniques and Applications (DICTA)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/DICTA.2017.8227501\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2017 International Conference on Digital Image Computing: Techniques and Applications (DICTA)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/DICTA.2017.8227501","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Digital and paper based documents co-exist in our daily lives. Seamless integration of information from both sources is crucial for efficient knowledge management. This paper address the algorithm that can handle the detection of document so that it can be captured easily to convert it into a digital form for automatic integration of relevant information in electronic work flows. It uses the deep learning technique to provide a solution which is more generalized and flexible than other available solutions.