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Handwritten historical document anal...

Fischer, Andreas.

Handwritten historical document analysis, recognition, and retrievalstate of the art and future trends /

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	Handwritten historical document analysis, recognition, and retrieval[edited by] Andreas Fischer, Marcus Liwicki, Rolf Ingold.
其他題名:	state of the art and future trends /
其他作者:	Fischer, Andreas.
出版者:	Singapore :World Scientific,c2021.
面頁冊數:	1 online resource (xiii, 254 p.)
附註:	Inlcudes index.
標題:	Optical pattern recognition.
電子資源:	https://www.worldscientific.com/worldscibooks/10.1142/11353#t=toc
ISBN:	9789811203244$q(ebook)

Handwritten historical document analysis, recognition, and retrievalstate of the art and future trends /
Handwritten historical document analysis, recognition, and retrievalstate of the art and future trends /[electronic resource] :[edited by] Andreas Fischer, Marcus Liwicki, Rolf Ingold. - 1st ed. - Singapore :World Scientific,c2021. - 1 online resource (xiii, 254 p.) - Series in machine perception and artificial intelligence ;v. 89. - Series in machine perception and artificial intelligence ;v. 74..

Inlcudes index.

"In recent years, libraries and archives all around the world have increased their efforts to digitize historical manuscripts. To integrate the manuscripts into digital libraries, pattern recognition and machine learning methods are needed to extract and index the contents of the scanned images. The unique compendium describes the outcome of the HisDoc research project, a pioneering attempt to study the whole processing chain of layout analysis, handwriting recognition, and retrieval of historical manuscripts. This description is complemented with an overview of other related research projects, in order to convey the current state of the art in the field and outline future trends. This must-have volume is a relevant reference work for librarians, archivists and computer scientists"--Publisher's website.

Mode of access: World Wide Web.

ISBN: 9789811203244$q(ebook)Subjects--Topical Terms:

188326
Optical pattern recognition.

LC Class. No.: TA1650 / .H36 2021

Dewey Class. No.: 006.42

Handwritten historical document analysis, recognition, and retrievalstate of the art and future trends /
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245 0 0 $a Handwritten historical document analysis, recognition, and retrieval $h [electronic resource] : $b state of the art and future trends / $c [edited by] Andreas Fischer, Marcus Liwicki, Rolf Ingold.
250 $a 1st ed.
260 $a Singapore : $b World Scientific, $c c2021.
300 $a 1 online resource (xiii, 254 p.)
490 1 $a Series in machine perception and artificial intelligence ; $v v. 89
500 $a Inlcudes index.
520 $a "In recent years, libraries and archives all around the world have increased their efforts to digitize historical manuscripts. To integrate the manuscripts into digital libraries, pattern recognition and machine learning methods are needed to extract and index the contents of the scanned images. The unique compendium describes the outcome of the HisDoc research project, a pioneering attempt to study the whole processing chain of layout analysis, handwriting recognition, and retrieval of historical manuscripts. This description is complemented with an overview of other related research projects, in order to convey the current state of the art in the field and outline future trends. This must-have volume is a relevant reference work for librarians, archivists and computer scientists"--Publisher's website.
538 $a Mode of access: World Wide Web.
538 $a System requirements: Adobe Acrobat Reader.
588 $a Description based on print version record.
650 0 $a Optical pattern recognition. $3 188326
650 0 $a Text processing (Computer science) $3 210527
650 0 $a Document imaging systems. $3 184308
650 0 $a Image analysis. $3 190419
650 0 $a Digital libraries. $3 184316
700 1 $a Fischer, Andreas. $3 835360
700 1 $a Liwicki, Marcus. $3 902700
700 1 $a Ingold, Rolf. $3 902701
830 0 $a Series in machine perception and artificial intelligence ; $v v. 74. $3 575154
856 4 0 $u https://www.worldscientific.com/worldscibooks/10.1142/11353#t=toc