Reading and learning : adaptive content recognition
The 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, i...
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| Médium: | Livre numérique |
| Jazyk: | Anglais |
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Berlin [etc.] :
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[20..].
Cham : Springer Nature |
| Edice: | Lecture notes in computer science
2956 |
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| On-line přístup: | Accès sur la plateforme de l'éditeur Accès sur la plateforme Istex Accès Université d'Orléans Accès INSA CVL |
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| Edition sous un autre format: | • Reading and learning, adaptive content recognition, Andreas Dengel, Markus Junker, Anette Weisbecker (eds.), Berlin, Springer, 2004, 1 vol. (XII-354 p.), Lecture notes in computer science, 3-540-21904-8 • Reading and Learning, Texte imprimé, 9783662180167 |
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| 100 | 1 | |a Dengel, Andreas. | |
| 245 | 1 | 0 | |a Reading and learning : |b adaptive content recognition |c [edited by] Andreas Dengel, Markus Junker, Anette Weisbecker. |
| 260 | |a Berlin [etc.] : |b Springer. | ||
| 260 | |a Cham : |b Springer Nature, |c [20..]. | ||
| 490 | 0 | |a Lecture notes in computer science |v 2956 |x 1611-3349 | |
| 500 | |a Archives Springer e-books (Licence nationale) | ||
| 500 | |a Archives Springer e-books (Licence nationale) | ||
| 505 | 0 | |a Error 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. | |
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| 506 | |a Conditions particulières de réutilisation pour les bénéficiaires des licences nationales. https://www.licencesnationales.fr/springer-nature-ebooks-contrat-licence-ln-2017 | ||
| 520 | |a The 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. | ||
| 650 | |a Informatique | ||
| 650 | |a Technologie de l'information | ||
| 650 | |a Intelligence artificielle | ||
| 650 | |a Traitement d'images | ||
| 650 | |a Perception des structures | ||
| 650 | |a Informatique documentaire | ||
| 650 | |a Traitement optique de l'information | ||
| 650 | |a Gestion de l'information | ||
| 700 | 1 | |a Junker, Markus. |4 pbd | |
| 700 | 1 | |a Weisbecker, Anette. |4 pbd | |
| 776 | 0 | |0 078865026 |t Reading and learning |o adaptive content recognition |f Andreas Dengel, Markus Junker, Anette Weisbecker (eds.) |c Berlin |n Springer |d 2004 |p 1 vol. (XII-354 p.) |s Lecture notes in computer science |z 3-540-21904-8 | |
| 776 | 0 | |t Reading and Learning |b Texte imprimé |z 9783662180167 | |
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