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Handwritten Digit Recognition with Neural Network
5th International Conference on Microelectronics and Telecommunication Engineering, ICMETE 2021 ; 373:525-532, 2022.
Article in English | Scopus | ID: covidwho-1750648
ABSTRACT
Object detection is the task of classifying and finding certain objects including people, cars, handwritten text, and more. This is a growing field with application in several fields, identifying and locating cars, pedestrians and other objects for self-driving cars, monitoring objects such as crops, or the ball during sports, facial detection for protection and many more. Handwritten text recognition comprises character recognition and digit recognition. An effective CNN based model with high accuracy can help an OCR (Optical Character Recognition) system for accurate conversion of written text into digital text. In this work, we have explained a CNN based approach for recognizing hand written digits and predict the written numbers. © 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.
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Full text: Available Collection: Databases of international organizations Database: Scopus Language: English Journal: 5th International Conference on Microelectronics and Telecommunication Engineering, ICMETE 2021 Year: 2022 Document Type: Article

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Full text: Available Collection: Databases of international organizations Database: Scopus Language: English Journal: 5th International Conference on Microelectronics and Telecommunication Engineering, ICMETE 2021 Year: 2022 Document Type: Article