LEADER 06315nam 22008535 450 001 9910144192103321 005 20200706125311.0 010 $a1-280-30735-8 010 $a9786610307357 010 $a3-540-24642-8 024 7 $a10.1007/b96988 035 $a(CKB)1000000000212360 035 $a(SSID)ssj0000232935 035 $a(PQKBManifestationID)11201116 035 $a(PQKBTitleCode)TC0000232935 035 $a(PQKBWorkID)10219405 035 $a(PQKB)10374849 035 $a(DE-He213)978-3-540-24642-8 035 $a(MiAaPQ)EBC3088310 035 $a(PPN)15521330X 035 $a(EXLCZ)991000000000212360 100 $a20121227d2004 u| 0 101 0 $aeng 135 $aurnn|008mamaa 181 $ctxt 182 $cc 183 $acr 200 10$aReading and Learning $eAdaptive Content Recognition /$fedited by Andreas Dengel, Markus Junker, Anette Weisbecker 205 $a1st ed. 2004. 210 1$aBerlin, Heidelberg :$cSpringer Berlin Heidelberg :$cImprint: Springer,$d2004. 215 $a1 online resource (XII, 356 p.) 225 1 $aLecture Notes in Computer Science,$x0302-9743 ;$v2956 300 $aBibliographic Level Mode of Issuance: Monograph 311 $a3-540-21904-8 320 $aIncludes bibliographical references at the end of each chapters and index. 327 $aError Tolerant Color Deskew -- Adaptive Threshold -- Neighbourhood Related Color Segmentation Based on a Fuzzy Color Classification TooL -- Improving Image Processing Systems by Artificial Neural Networks -- Adaptive Segmentation of Multicoloured Documents without a Marked Background -- Recognition of Short Handwritten Texts -- Handwritten Address Recognition Using Hidden Markov Models -- Adaptive Combination of Commercial OCR Systems -- Component-Based Software Engineering Methods for Systems in Document Recognition, Analysis, and Understanding -- A Component-Based Framework for Recognition Systems -- smartFIX: An Adaptive System for Document Analysis and Understanding -- How Postal Address Readers Are Made Adaptive -- A Tool for Semi-automatic Document Reengineering -- Inspecting Document Collections -- Introducing Query Expansion Methods for Collaborative Information Retrieval -- Improving Document Transformation Techniques with Collaborative Learned Term-Based Concepts -- Passage Retrieval Based on Density Distributions of Terms and Its Applications to Document Retrieval and Question Answering -- Results of a Survey about the Use of Tools in the Area of Document Management. 330 $aThe amounts of information that are ?ooding people both at the workplace and in private life have increased dramatically in the past ten years. The number of paper documents doubles every four years, and the amount of information stored on all data carriers every six years. New knowledge, however, increases at a considerably lower rate. Possibilities for automatic content recognition in various media and for the processing of documents are therefore becoming more important every day. Especially in economic terms, the e?cient handling of information, i.e., ?- ing the right information at the right time, is an invaluable resource for any enterprise, but it is particularly important for small- and medium-sized ent- prises. The market for document management systems, which in Europe had a volume of approximately 5 billion euros in 2000, will increase considerably over the next few years. The BMBF recognized this development at an early stage. As early as in 1995, it pooled national capabilities in this ?eld in order to support research on the automatic processing of information within the framework of a large collaborative project (READ) involving both industrial companies and research centres. Evaluation of the results led to the conclusion that research work had been successful, and, in a second phase, funding was provided for the colla- rative follow-up project Adaptive READ from 1999 to 2003. The completion of thesetwoimportantlong-termresearchprojectshascontributedsubstantiallyto improving the possibilities of content recognition and processing of handwritten, printed and electronic documents. 410 0$aLecture Notes in Computer Science,$x0302-9743 ;$v2956 606 $aArtificial intelligence 606 $aPattern recognition 606 $aInformation storage and retrieval 606 $aApplication software 606 $aNatural language processing (Computer science) 606 $aOptical data processing 606 $aArtificial Intelligence$3https://scigraph.springernature.com/ontologies/product-market-codes/I21000 606 $aPattern Recognition$3https://scigraph.springernature.com/ontologies/product-market-codes/I2203X 606 $aInformation Storage and Retrieval$3https://scigraph.springernature.com/ontologies/product-market-codes/I18032 606 $aInformation Systems Applications (incl. Internet)$3https://scigraph.springernature.com/ontologies/product-market-codes/I18040 606 $aNatural Language Processing (NLP)$3https://scigraph.springernature.com/ontologies/product-market-codes/I21040 606 $aImage Processing and Computer Vision$3https://scigraph.springernature.com/ontologies/product-market-codes/I22021 615 0$aArtificial intelligence. 615 0$aPattern recognition. 615 0$aInformation storage and retrieval. 615 0$aApplication software. 615 0$aNatural language processing (Computer science). 615 0$aOptical data processing. 615 14$aArtificial Intelligence. 615 24$aPattern Recognition. 615 24$aInformation Storage and Retrieval. 615 24$aInformation Systems Applications (incl. Internet). 615 24$aNatural Language Processing (NLP). 615 24$aImage Processing and Computer Vision. 676 $a658.4038 702 $aDengel$b Andreas$4edt$4http://id.loc.gov/vocabulary/relators/edt 702 $aJunker$b Markus$4edt$4http://id.loc.gov/vocabulary/relators/edt 702 $aWeisbecker$b Anette$4edt$4http://id.loc.gov/vocabulary/relators/edt 712 02$aAdaptive READ (Project) 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910144192103321 996 $aReading and Learning$91935983 997 $aUNINA