Contribution on Arabic Handwriting Recognition Using Deep Neural Network

2020 ◽  
pp. 123-133
Author(s):  
Zouhaira Noubigh ◽  
Anis Mezghani ◽  
Monji Kherallah
Keyword(s):  
Neural Network ◽  
Deep Neural Network ◽  
Handwriting Recognition

scholarly journals Hiragana Handwriting Recognition Using Deep Neural Network Search

2020 ◽  
Vol 14 (01) ◽  
pp. 161
Author(s):  
Rosalina Rosalina ◽  
Johanes Parlindungan Hutagalung ◽  
Genta Sahuri
Keyword(s):  
Neural Network ◽  
Social Media ◽  
Deep Neural Network ◽  
Handwriting Recognition ◽  
Text Recognition ◽  
Android Application ◽  
Network Search ◽  
Handwritten Text ◽  
Handwritten Text Recognition ◽  
Computer Storage

<span id="orcid-id" class="orcid-id-https">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. </span>

scholarly journals Vietnamese handwritten character recognition using convolutional neural network

2020 ◽  
Vol 9 (2) ◽  
pp. 276
Author(s):  
Truong Quang Vinh ◽  
Le Hoai Duy ◽  
Nguyen Thanh Nhan
Keyword(s):  
Neural Network ◽  
Character Recognition ◽  
High Performance ◽  
Deep Neural Network ◽  
Handwriting Recognition ◽  
Real Word ◽  
The Core ◽  
Fully Connected ◽  
Drop Rate ◽  
Overfitting Problem

Handwriting recognition is one of the core applications of computer vision for real-word problems and it has been gaining more interest because of the progression in this field. This paper presents an efficient model for Vietnamese handwriting character recognition by Convolutional Neural Networks (CNNs) – a kind of deep neural network model can achieve high performance on hard recognition tasks. The proposed architecture of the CNN network for Vietnamese handwriting character recognition consists of five hidden layers in which the first 3 layers are convolutional layers and the last 2 layers are fully-connected layers. Overfitting problem is also minimized by using dropout techniques with the reasonable drop rate. The experimental results show that our model achieves approximately 97% accuracy.

Deep Neural Network Classification of I-123 Ioflupane SPECT

2020 ◽  
Author(s):  
David T. Wang ◽  
Brady Williamson ◽  
Thomas Eluvathingal ◽  
Bruce Mahoney ◽  
Jennifer Scheler
Keyword(s):  
Neural Network ◽  
Deep Neural Network ◽  
Neural Network Classification

Method of determination of the text direction on the image with the use of convolutional neural network

2020 ◽  
pp. 96-99
Author(s):  
P.L. Nikolaev
Keyword(s):  
Neural Network ◽  
Convolutional Neural Network ◽  
Deep Neural Network ◽  
Binary Classification ◽  
Synthetic Data ◽  
Real Data ◽  
Method Of Determination ◽  
Classification Of Images

This article deals with method of binary classification of images with small text on them Classification is based on the fact that the text can have 2 directions – it can be positioned horizontally and read from left to right or it can be turned 180 degrees so the image must be rotated to read the sign. This type of text can be found on the covers of a variety of books, so in case of recognizing the covers, it is necessary first to determine the direction of the text before we will directly recognize it. The article suggests the development of a deep neural network for determination of the text position in the context of book covers recognizing. The results of training and testing of a convolutional neural network on synthetic data as well as the examples of the network functioning on the real data are presented.

Underwater Fish Images Classification by Deep Neural Network

2020 ◽  
Author(s):  
Ala Supriya ◽  
Chiluka Venkat ◽  
Aliketti Deepak ◽  
GV Hari Prasad
Keyword(s):  
Neural Network ◽  
Deep Neural Network
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