.png){kind=logo}
Stock image for illustration purposes only - book cover, edition or condition may vary.
Machine Learning in Document Analysis and Recognition
. Ed(S): Marinai, Simone; Fujisawa, Hiromichi
€ 196.65
FREE Delivery in Ireland
Description for Machine Learning in Document Analysis and Recognition
Hardback. The objective of Document Analysis and Recognition (DAR) is to recognize the text and graphical components of a document and to extract information. This book identifies good practices for the use of learning strategies in DAR, and identifies DAR tasks that are more appropriate for these techniques. Editor(s): Marinai, Simone; Fujisawa, Hiromichi. Series: Studies in Computational Intelligence. Num Pages: 434 pages, 142 black & white illustrations, 41 black & white tables, biography. BIC Classification: PBW; UYQM. Category: (UP) Postgraduate, Research & Scholarly. Dimension: 239 x 157 x 20. Weight in Grams: 768.
The objective of Document Analysis and Recognition (DAR) is to recognize the text and graphicalcomponents of a document and to extract information. With ?rst papers dating back to the 1960’s, DAR is a mature but still gr- ing research?eld with consolidated and known techniques. Optical Character Recognition (OCR) engines are some of the most widely recognized pr- ucts of the research in this ?eld, while broader DAR techniques are nowadays studied and applied to other industrial and o?ce automation systems. In the machine learning community, one of the most widely known - search problems addressed in DAR is recognition of ... Read more
The objective of Document Analysis and Recognition (DAR) is to recognize the text and graphicalcomponents of a document and to extract information. With ?rst papers dating back to the 1960’s, DAR is a mature but still gr- ing research?eld with consolidated and known techniques. Optical Character Recognition (OCR) engines are some of the most widely recognized pr- ucts of the research in this ?eld, while broader DAR techniques are nowadays studied and applied to other industrial and o?ce automation systems. In the machine learning community, one of the most widely known - search problems addressed in DAR is recognition of ... Read more
Product Details
Format
Hardback
Publication date
2008
Publisher
Springer-Verlag Berlin and Heidelberg GmbH & Co. KG Germany
Number of pages
434
Condition
New
Series
Studies in Computational Intelligence
Number of Pages
434
Place of Publication
Berlin, Germany
ISBN
9783540762799
SKU
V9783540762799
Shipping Time
Usually ships in 15 to 20 working days
Ref
99-15
Reviews for Machine Learning in Document Analysis and Recognition