Ubiquitous Document Capturing with Deep Learning

被引：0

作者：

Naz, Tayyaha ^{[1
]}

Khan, Anain Ahinad ^{[1
]}

Shafait, Faisal ^{[1
]}

机构：

[1] Natl Univ Sci & Technol, Sch Elect Engn & Comp Sci, Islamabad, Pakistan

来源：

2017 INTERNATIONAL CONFERENCE ON DIGITAL IMAGE COMPUTING - TECHNIQUES AND APPLICATIONS (DICTA) | 2017年

关键词：

Document capture; Document detection; Machine learning; Deep learning; CNN; LSD;

D O I：

暂无

中图分类号：

TM [电工技术]; TN [电子技术、通信技术];

学科分类号：

0808 ; 0809 ;

摘要：

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.

引用

页码：799 / 806

页数：8

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