Recognition Of Whiteboard Notes: Online, Offline And Combination
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| Title: | Recognition Of Whiteboard Notes: Online, Offline And Combination |
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| 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) |
| Abstract: | 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%. |
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| ISBN: | 9789812814531 9789812814548 |
