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Handwriting recognition (HWR) is the ability of a computer to accept and interpret comprehensible handwritten input from sources such as paper documents, pictures, touch-screens, and other devices. Handwritten text recognition (HTR) is another name for handwriting recognition. Handwriting recognition (HWR) is also known as handwritten text recognition (HTR). By using optical scanning or intelligent word recognition, the image of the written text can be sensed "off line" from a piece of paper. This can be done in a number of different ways. A different option is for the movements of the pen tip to be sensed "on line," for instance by a pen-based computer screen surface. This is a task that is typically simpler because there are more hints available. Formatting, accurate character segmentation, and the identification of words that are most likely to be written are all taken care of by a handwriting recognition system.
How You Will Benefit
(I) Insights, and validations about the following topics:
Chapter 1: Handwriting Recognition
Chapter 2: Artificial Neural Network
Chapter 3: Optical Character Recognition
Chapter 4: Recurrent Neural Network
Chapter 5: Long Short-term Memory
Chapter 6: Deep Learning
Chapter 7: Signature Recognition
Chapter 8: Handwritten Biometric Recognition
Chapter 9: MNIST Database
Chapter 10: History of Artificial Neural Networks
(II) Answering the public top questions about handwriting recognition.
(III) Real world examples for the usage of handwriting recognition in many fields.
(IV) 17 appendices to explain, briefly, 266 emerging technologies in each industry to have 360-degree full understanding of handwriting recognition' technologies.
Who This Book Is For
Professionals, undergraduate and graduate students, enthusiasts, hobbyists, and those who want to go beyond basic knowledge or information for any kind of handwriting recognition.
