machine learning models of handwritten character recognition (Paperback)
Language: English
Published by Savage, 2026
- Softcover
- New

Seller: CitiRetail, Stevenage, United KingdomCitiRetail
AbeBooks seller since June 29, 2022
Condition: New
US$ 27.53
Quantity: 1 available
Add to basketItem description from seller
Paperback. Document Analysis and Recognition (DAR) systems play a critical role in enabling this data exchange. A key component of DAR systems is Optical Character Recognition (OCR), which allows for the recognition of both printed and handwritten text. Handwritten text recognition systems are especially valuable, providing a seamless interface that enhances communication between users and computers, enabling machines to interpret and process handwritten documents. Such systems contribute substantially to bridging the gap between humans and machines. Although considerable research has focused on recognizing characters in Indian scripts, the challenge of efficient data exchange between humans and machines remains unresolved for these scripts. This book addresses these challenges by developing a framework for predicting age, gender, and handedness in handwritten character recognition of the Gurumukhi script, which is used for the Punjabi language, one of India's official languages. Notably, Gurumukhi is the tenth most widely used script globally. It uses feature extraction techniques, performance evaluation metrics in age, gender and handedness, and explores various methods using machine learning models/ neural networks for recognition of indic and non-indic scripts. This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability. …
Seller Inventory # 9798182724272
- Title
- machine learning models of handwritten character recognition (Paperback)
- Author
- Jt Savage
- Publisher
- Savage
- Publication year
- 2026
- Condition
- new
- Binding
- Paperback
- Language
- English
- ISBN 13
- 9798182724272
Document Analysis and Recognition (DAR) systems play a critical role in enabling this data exchange. A key component of DAR systems is Optical Character Recognition (OCR), which allows for the recognition of both printed and handwritten text. Handwritten text recognition systems are especially valuable, providing a seamless interface that enhances communication between users and computers, enabling machines to interpret and process handwritten documents. Such systems contribute substantially to bridging the gap between humans and machines. Although considerable research has focused on recognizing characters in Indian scripts, the challenge of efficient data exchange between humans and machines remains unresolved for these scripts. This book addresses these challenges by developing a framework for predicting age, gender, and handedness in handwritten character recognition of the Gurumukhi script, which is used for the Punjabi language, one of India's official languages. Notably, Gurumukhi is the tenth most widely used script globally. It uses feature extraction techniques, performance evaluation metrics in age, gender and handedness, and explores various methods using machine learning models/ neural networks for recognition of indic and non-indic scripts.
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CitiRetail
Stevenage, United Kingdom
AbeBooks seller since June 29, 2022
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