Hiragana Handwriting Recognition Using Deep Neural Network Search
Dublin Core
Title
Hiragana Handwriting Recognition Using Deep Neural Network Search
Subject
Hiragana
Handwriting Recognition
Deep Neural Network Search
Android
Real-time
Description
These days there is a huge demand in “storing the information available in paper documents into a computer storage disk”. Digitizing manual filled forms lead to handwriting recognition, a process of translating handwriting into machine editable text. The main objective of this research is to to create an Android application able to recognize and predict the output of handwritten characters by training a neural network model. This research will implement deep neural network in recognizing handwritten text recognition especially to recognize digits, Latin / Alphabet and Hiragana, capture an image or choose the image from gallery to scan the handwritten text from the image, use the live camera to detect the handwritten text real – time without capturing an image and could copy the results of the output from the off-line recognition and share it to other platforms such as notes, Email, and social media.
Creator
rosalina, Rosalina
Hutagalung, Johanes Parlindungan
Sahuri, Genta
Source
International Journal of Interactive Mobile Technologies (iJIM); Vol. 14 No. 01 (2020); pp. 161-168
1865-7923
Publisher
International Association of Online Engineering (IAOE), Vienna, Austria
Date
2020-01-20
Rights
Copyright (c) 2020 Rosalina rosalina
Relation
Format
application/pdf
Language
eng
Type
info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
Non-refereed Article
Identifier
Citation
Rosalina rosalina, Johanes Hutagalung Parlindungan and Genta Sahuri, Hiragana Handwriting Recognition Using Deep Neural Network Search, International Association of Online Engineering (IAOE), Vienna, Austria, 2020, accessed November 8, 2024, https://igi.indrastra.com/items/show/1577