UGC Approved Journal no 63975(19)

ISSN: 2349-5162 | ESTD Year : 2014
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Published in:

Volume 9 Issue 4
April-2022
eISSN: 2349-5162

UGC and ISSN approved 7.95 impact factor UGC Approved Journal no 63975

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Published Paper ID:
JETIR2204429


Registration ID:
400756

Page Number

e202-e205

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Title

HANDWRITTEN RECOGNITION SYSTEM USING DEEP LEARNING

Abstract

Recent advances in the fields of image processing and natural language processing have centered on constructing smart systems to improve people's quality of life. In this paper, an effective method for text detection and extraction from photographs, as well as text to audio conversion, is proposed. Handwriting detection is a computer technology or capability for receiving and interpreting comprehensible handwritten input from sources such as paper documents, touch screens, photo graphs, and so on. Handwritten One type of area pattern recognition is text recognition. Pattern recognition is used to categorize or classify data or objects into one of several classes or categories. The task of translating a language expressed in its spatial form of graphical marks into its symbolic representation is defined as handwriting recognition. Each script comprises a set of icons known as characters or letters, each of which has a fundamental shape. Handwriting's purpose is to correctly identify input characters or images, which are subsequently examined by a variety of automated process systems. This technology will be used to detect various types of writings. Handwriting has advanced to the point where numerous types of handwritten characters, such as digits, numerals, cursive script, symbols, and scripts in English and other languages, can be discovered. Automatic handwritten text recognition can be extremely useful in a variety of applications where large volumes of handwritten data must be processed, such as the recognition of addresses and postcodes on envelopes, the interpretation of amounts on bank checks, document analysis, and signature verification. As a result, a computer is required to read documents or data in order to facilitate document processing.

Key Words

NLP -Natural Language Processing, CNN – Convolutional Neural Network, OCR - Optical Character Recognition.

Cite This Article

"HANDWRITTEN RECOGNITION SYSTEM USING DEEP LEARNING ", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.9, Issue 4, page no.e202-e205, April-2022, Available :http://www.jetir.org/papers/JETIR2204429.pdf

ISSN


2349-5162 | Impact Factor 7.95 Calculate by Google Scholar

An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 7.95 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator

Cite This Article

"HANDWRITTEN RECOGNITION SYSTEM USING DEEP LEARNING ", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.9, Issue 4, page no. ppe202-e205, April-2022, Available at : http://www.jetir.org/papers/JETIR2204429.pdf

Publication Details

Published Paper ID: JETIR2204429
Registration ID: 400756
Published In: Volume 9 | Issue 4 | Year April-2022
DOI (Digital Object Identifier):
Page No: e202-e205
Country: Pune, Maharashtra, India .
Area: Engineering
ISSN Number: 2349-5162
Publisher: IJ Publication


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