Attributed point matching for automatic groundtruth generation

IF 1.8 4区 计算机科学 Q3 COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE
Doe-Wan Kim, T. Kanungo
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引用次数: 14
用于自动地真生成的归属点匹配
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来源期刊
International Journal on Document Analysis and Recognition
International Journal on Document Analysis and Recognition 工程技术-计算机:人工智能
CiteScore
6.20
自引率
4.30%
发文量
30
审稿时长
7.5 months
期刊介绍: The large number of existing documents and the production of a multitude of new ones every year raise important issues in efficient handling, retrieval and storage of these documents and the information which they contain. This has led to the emergence of new research domains dealing with the recognition by computers of the constituent elements of documents - including characters, symbols, text, lines, graphics, images, handwriting, signatures, etc. In addition, these new domains deal with automatic analyses of the overall physical and logical structures of documents, with the ultimate objective of a high-level understanding of their semantic content. We have also seen renewed interest in optical character recognition (OCR) and handwriting recognition during the last decade. Document analysis and recognition are obviously the next stage. Automatic, intelligent processing of documents is at the intersections of many fields of research, especially of computer vision, image analysis, pattern recognition and artificial intelligence, as well as studies on reading, handwriting and linguistics. Although quality document related publications continue to appear in journals dedicated to these domains, the community will benefit from having this journal as a focal point for archival literature dedicated to document analysis and recognition.
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