Articoli correlati a Machine Learning in Document Analysis and Recognition:...
Sinossi
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 is a collection of research papers and state-of-the-art reviews by leading researchers all over the world. It includes pointers to challenges and opportunities for future research directions. The main goal of the book is to identify good practices for the use of learning strategies in DAR.
Le informazioni nella sezione "Riassunto" possono far riferimento a edizioni diverse di questo titolo.
Contenuti
to Document Analysis and Recognition.- Structure Extraction in Printed Documents Using Neural Approaches.- Machine Learning for Reading Order Detection in Document Image Understanding.- Decision-Based Specification and Comparison of Table Recognition Algorithms.- Machine Learning for Digital Document Processing: from Layout Analysis to Metadata Extraction.- Classification and Learning Methods for Character Recognition: Advances and Remaining Problems.- Combining Classifiers with Informational Confidence.- Self-Organizing Maps for Clustering in Document Image Analysis.- Adaptive and Interactive Approaches to Document Analysis.- Cursive Character Segmentation Using Neural Network Techniques.- Multiple Hypotheses Document Analysis.- Learning Matching Score Dependencies for Classifier Combination.- Perturbation Models for Generating Synthetic Training Data in Handwriting Recognition.- Review of Classifier Combination Methods.- Machine Learning for Signature Verification.- Off-line Writer Identification and Verification Using Gaussian Mixture Models.
Product Description
Book by Marinai Simone
Le informazioni nella sezione "Su questo libro" possono far riferimento a edizioni diverse di questo titolo.
Compra nuovo
Visualizza questo articolo
EUR 96,06
GRATIS per la spedizione da U.S.A. a Italia
Destinazione, tempi e costi
Risultati della ricerca per Machine Learning in Document Analysis and Recognition:...
Foto dell'editore
Machine Learning in Document Analysis and Recognition (Studies in Computational Intelligence, 90)
Da: Phatpocket Limited, Waltham Abbey, HERTS, Regno Unito
Valutazione del venditore 5 su 5 stelle
Condizione: Good. Your purchase helps support Sri Lankan Children's Charity 'The Rainbow Centre'. Ex-library, so some stamps and wear, but in good overall condition. Our donations to The Rainbow Centre have helped provide an education and a safe haven to hundreds of children who live in appalling conditions. Codice articolo Z1-ZZ-001-00190
Quantità: 1 disponibili
Foto dell'editore
Machine Learning In Document Analysis And Recognition
Da: Basi6 International, Irving, TX, U.S.A.
Valutazione del venditore 5 su 5 stelle
Condizione: Brand New. New. US edition. Expediting shipping for all USA and Europe orders excluding PO Box. Excellent Customer Service. Codice articolo ABEJUNE24-270425
Quantità: 1 disponibili
Foto dell'editore
Machine Learning In Document Analysis And Recognition
Da: Romtrade Corp., STERLING HEIGHTS, MI, U.S.A.
Valutazione del venditore 5 su 5 stelle
Condizione: New. This is a Brand-new US Edition. This Item may be shipped from US or any other country as we have multiple locations worldwide. Codice articolo ABNR-87890
Quantità: 1 disponibili
Foto dell'editore
Machine Learning in Document Analysis and Recognition (Studies in Computational Intelligence, 90)
Da: ALLBOOKS1, Direk, SA, Australia
Valutazione del venditore 5 su 5 stelle
Codice articolo SHUB270425
Quantità: 1 disponibili
Foto dell'editore
Machine Learning in Document Analysis and Recognition
Da: Books Puddle, New York, NY, U.S.A.
Valutazione del venditore 4 su 5 stelle
Condizione: New. pp. 448. Codice articolo 26304987
Quantità: 1 disponibili
Foto dell'editore
Machine Learning in Document Analysis and Recognition
Da: Majestic Books, Hounslow, Regno Unito
Valutazione del venditore 5 su 5 stelle
Condizione: New. pp. 448 52:B&W 6.14 x 9.21in or 234 x 156mm (Royal 8vo) Case Laminate on White w/Gloss Lam. Codice articolo 7542916
Quantità: 1 disponibili
Foto dell'editore
Machine Learning in Document Analysis and Recognition
Da: Biblios, Frankfurt am main, HESSE, Germania
Valutazione del venditore 5 su 5 stelle
Condizione: New. pp. 448. Codice articolo 18304977
Quantità: 1 disponibili
Immagini fornite dal venditore
Machine Learning in Document Analysis and Recognition
Editore:
Springer Berlin Heidelberg Jan 2008, 2008
ISBN 10: 3540762795
ISBN 13: 9783540762799
Nuovo
Rilegato
Da: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Germania
Valutazione del venditore 5 su 5 stelle
Buch. Condizione: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -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 is a collection of research papers and state-of-the-art reviews by leading researchers all over the world. It includes pointers to challenges and opportunities for future research directions. The main goal of the book is to identify good practices for the use of learning strategies in DAR. 448 pp. Englisch. Codice articolo 9783540762799
Quantità: 2 disponibili
Immagini fornite dal venditore
Machine Learning in Document Analysis and Recognition
Da: AHA-BUCH GmbH, Einbeck, Germania
Valutazione del venditore 5 su 5 stelle
Buch. Condizione: Neu. Druck auf Anfrage Neuware - Printed after ordering - 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 unconstrained handwr- ten characters which has been frequently used in the past as a benchmark for evaluating machine learning algorithms, especially supervised classi ers. However, developing a DAR system is a complex engineering task that involves the integration of multiple techniques into an organic framework. A reader may feel that the use of machine learning algorithms is not approp- ate for other DAR tasks than character recognition. On the contrary, such algorithms have been massively used for nearly all the tasks in DAR. With large emphasis being devoted to character recognition and word recognition, other tasks such as pre-processing, layout analysis, character segmentation, and signature veri cation have also bene ted much from machine learning algorithms. Codice articolo 9783540762799
Quantità: 1 disponibili
Immagini fornite dal venditore
Machine Learning in Document Analysis and Recognition
ISBN 10: 3540762795
ISBN 13: 9783540762799
Nuovo
Rilegato
Da: buchversandmimpf2000, Emtmannsberg, BAYE, Germania
Valutazione del venditore 5 su 5 stelle
Buch. Condizione: Neu. Neuware -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 unconstrained handwr- ten characters which has been frequently used in the past as a benchmark for evaluating machine learning algorithms, especially supervised classi ers. However, developing a DAR system is a complex engineering task that involves the integration of multiple techniques into an organic framework. A reader may feel that the use of machine learning algorithms is not approp- ate for other DAR tasks than character recognition. On the contrary, such algorithms have been massively used for nearly all the tasks in DAR. With large emphasis being devoted to character recognition and word recognition, other tasks such as pre-processing, layout analysis, character segmentation, and signature veri cation have also bene ted much from machine learning algorithms.Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg 448 pp. Englisch. Codice articolo 9783540762799
Quantità: 2 disponibili