scholarly journals Offline Handwritten Text Recognition Using Deep Learning: A Review

2021 ◽  
Vol 1848 (1) ◽  
pp. 012015
Author(s):  
Yintong Wang ◽  
Wenjie Xiao ◽  
Shuo Li
Keyword(s):  
Deep Learning ◽  
Text Recognition ◽  
Handwritten Text ◽  
Handwritten Text Recognition

scholarly journals Handwritten Text Recognition using Deep Learning with TensorFlow

2020 ◽  
Vol V9 (05) ◽  
Author(s):  
Sri. Yugandhar Manchala ◽  
Jayaram Kinthali ◽  
Kowshik Kotha ◽  
Kanithi Santosh Kumar, Jagilinki Jayalaxmi ◽  
Keyword(s):  
Deep Learning ◽  
Text Recognition ◽  
Handwritten Text ◽  
Handwritten Text Recognition

HTR-Flor: A Deep Learning System for Offline Handwritten Text Recognition

2020 ◽  
Author(s):  
Arthur Flor de Sousa Neto ◽  
Byron Leite Dantas Bezerra ◽  
Alejandro Hector Toselli ◽  
Estanislau Baptista Lima
Keyword(s):  
Deep Learning ◽  
Learning System ◽  
Text Recognition ◽  
Handwritten Text ◽  
Handwritten Text Recognition

Handwritten Text Recognition and Conversion Using Convolutional Neural Network (CNN) Based Deep Learning Model

2021 ◽  
Author(s):  
Jebaveerasingh Jebadurai ◽  
Immanuel Johnraja Jebadurai ◽  
Getzi Jeba Leelipushpam Paulraj ◽  
Sushen Vallabh Vangeepuram
Keyword(s):  
Neural Network ◽  
Deep Learning ◽  
Convolutional Neural Network ◽  
Learning Model ◽  
Text Recognition ◽  
Handwritten Text ◽  
Handwritten Text Recognition ◽  
Deep Learning Model

scholarly journals A compact deep learning model for Khmer handwritten text recognition

2021 ◽  
Vol 10 (3) ◽  
pp. 584
Author(s):  
Bayram Annanurov ◽  
Norliza Noor
Keyword(s):  
Deep Learning ◽  
High Performance ◽  
Ad Hoc ◽  
Recognition Rate ◽  
Learning Model ◽  
Text Recognition ◽  
Handwritten Text ◽  
Handwritten Text Recognition ◽  
Fully Connected ◽  
Deep Learning Model

<p>The motivation of this study is to develop a compact offline recognition model for Khmer handwritten text that would be successfully applied under limited access to high-performance computational hardware. Such a task aims to ease the ad-hoc digitization of vast handwritten archives in many spheres. Data collected for previous experiments were used in this work. The oneagainst-all classification was completed with state-of-the-art techniques. A compact deep learning model (2+1CNN), with two convolutional layers and one fully connected layer, was proposed. The recognition rate came out to be within 93-98%. The compact model is performed on par with the state-of-theart models. It was discovered that computational capacity requirements usually associated with deep learning can be alleviated, therefore allowing applications under limited computational power.</p>

Handwritten Text Recognition using Deep Learning (CNN & RNN)

2021 ◽  
Vol 8 (6) ◽  
pp. 870-881
Author(s):  
Rohini G. Khalkar ◽  
Adarsh Singh Dikhit ◽  
Anirudh Goel
Keyword(s):  
Deep Learning ◽  
Text Recognition ◽  
Handwritten Text ◽  
Handwritten Text Recognition

scholarly journals Classification of Handwritten Names of Cities and Handwritten Text Recognition using Various Deep Learning Models

2020 ◽  
Vol 5 (5) ◽  
pp. 934-943
Author(s):  
Daniyar Nurseitov ◽  
Kairat Bostanbekov ◽  
Anel Alimova ◽  
Abdelrahman Abdallah ◽  
Galymzhan Abdimanap
Keyword(s):  
Deep Learning ◽  
Text Recognition ◽  
Learning Models ◽  
Handwritten Text ◽  
Handwritten Text Recognition
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