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Recognition Of Whiteboard Notes: Online, Offline And Combination

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Title: Recognition Of Whiteboard Notes: Online, Offline And Combination
Description: This book addresses the task of processing online handwritten notes acquired from an electronic whiteboard, which is a new modality in handwriting recognition research. The main motivation of this book is smart meeting rooms, aim to automate standard tasks usually performed by humans in a meeting.The book can be summarized as follows. A new online handwritten database is compiled, and four handwriting recognition systems are developed. Moreover, novel preprocessing and normalization strategies are designed especially for whiteboard notes and a new neural network based recognizer is applied. Commercial recognition systems are included in a multiple classifier system. The experimental results on the test set show a highly significant improvement of the recognition performance to more than 86%.
Authors: Horst Bunke, Marcus Liwicki
Resource Type: eBook.
Subjects: Image processing--Digital techniques, Optical pattern recognition, Writing--Data processing, Interactive whiteboards
Categories: COMPUTERS / Computer Science, COMPUTERS / Artificial Intelligence / Computer Vision & Pattern Recognition
Database: eBook Collection (EBSCOhost)
FullText Links:
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Text:
  Availability: 0
Header DbId: nlebk
DbLabel: eBook Collection (EBSCOhost)
An: 521164
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PubType: eBook
PubTypeId: ebook
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  Label: Title
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  Data: Recognition Of Whiteboard Notes: Online, Offline And Combination
– Name: Abstract
  Label: Description
  Group: Ab
  Data: This book addresses the task of processing online handwritten notes acquired from an electronic whiteboard, which is a new modality in handwriting recognition research. The main motivation of this book is smart meeting rooms, aim to automate standard tasks usually performed by humans in a meeting.The book can be summarized as follows. A new online handwritten database is compiled, and four handwriting recognition systems are developed. Moreover, novel preprocessing and normalization strategies are designed especially for whiteboard notes and a new neural network based recognizer is applied. Commercial recognition systems are included in a multiple classifier system. The experimental results on the test set show a highly significant improvement of the recognition performance to more than 86%.
– Name: Author
  Label: Authors
  Group: Au
  Data: <searchLink fieldCode="AR" term="%22Horst+Bunke%22">Horst Bunke</searchLink><br /><searchLink fieldCode="AR" term="%22Marcus+Liwicki%22">Marcus Liwicki</searchLink>
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  Data: <searchLink fieldCode="DE" term="%22Image+processing--Digital+techniques%22">Image processing--Digital techniques</searchLink><br /><searchLink fieldCode="DE" term="%22Optical+pattern+recognition%22">Optical pattern recognition</searchLink><br /><searchLink fieldCode="DE" term="%22Writing--Data+processing%22">Writing--Data processing</searchLink><br /><searchLink fieldCode="DE" term="%22Interactive+whiteboards%22">Interactive whiteboards</searchLink>
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RecordInfo BibRecord:
  BibEntity:
    Classifications:
      – Code: 006.42
        Scheme: ddc
        Type: prePub
    Languages:
      – Code: eng
        Text: English
    Subjects:
      – SubjectFull: Image processing--Digital techniques
        Type: general
      – SubjectFull: Optical pattern recognition
        Type: general
      – SubjectFull: Writing--Data processing
        Type: general
      – SubjectFull: Interactive whiteboards
        Type: general
    Titles:
      – TitleFull: Recognition Of Whiteboard Notes: Online, Offline And Combination
        Type: main
  BibRelationships:
    HasContributorRelationships:
      – PersonEntity:
          Name:
            NameFull: Horst Bunke
      – PersonEntity:
          Name:
            NameFull: Marcus Liwicki
      – PersonEntity:
          Name:
            NameFull: Horst Bunke
      – PersonEntity:
          Name:
            NameFull: Marcus Liwicki
    IsPartOfRelationships:
      – BibEntity:
          Dates:
            – D: 01
              M: 01
              Type: published
              Y: 2008
            – D: 04
              M: 02
              Type: profile
              Y: 2014
          Identifiers:
            – Type: isbn-print
              Value: 9789812814531
            – Type: isbn-electronic
              Value: 9789812814548
          Numbering:
            – Type: volume
              Value: 00071
          Titles:
            – TitleFull: Recognition Of Whiteboard Notes: Online, Offline And Combination
              Type: main
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