Arabic handwritten recognition using deep learning: A survey
N Alrobah, S Albahli - Arabian Journal for Science and Engineering, 2022 - Springer
In recent times, many research projects and experiments target machines that automatically
recognize handwritten characters, but most of them are done in Latin. Recognizing …
recognize handwritten characters, but most of them are done in Latin. Recognizing …
Multilingual handwritten numeral recognition using a robust deep network joint with transfer learning
Numeral recognition plays a crucial role in creating automated systems such as posting
address sorting and license plate recognition. Nowadays, numeral recognition systems …
address sorting and license plate recognition. Nowadays, numeral recognition systems …
Unsupervised writer adaptation for synthetic-to-real handwritten word recognition
Abstract Handwritten Text Recognition (HTR) is still a challenging problem because it must
deal with two important difficulties: the variability among writing styles, and the scarcity of …
deal with two important difficulties: the variability among writing styles, and the scarcity of …
iiit-indic-hw-words: A Dataset for Indic Handwritten Text Recognition
Handwritten text recognition (htr) for Indian languages is not yet a well-studied problem. This
is primarily due to the unavailability of large annotated datasets in the associated scripts …
is primarily due to the unavailability of large annotated datasets in the associated scripts …
Boosting handwriting text recognition in small databases with transfer learning
JCA Jaramillo, JJ Murillo-Fuentes… - 2018 16th International …, 2018 - ieeexplore.ieee.org
In this paper we deal with the offline handwriting text recognition (HTR) problem with
reduced training data sets. Recent HTR solutions based on artificial neural networks exhibit …
reduced training data sets. Recent HTR solutions based on artificial neural networks exhibit …
A pragmatic convolutional bagging ensemble learning for recognition of Farsi handwritten digits
Recognition of handwritten digits is one of the most important and challenging issues in
recent decades in the field of computer science. Its cursive nature, the right to left writing …
recent decades in the field of computer science. Its cursive nature, the right to left writing …
An end-to-end deep learning system for medieval writer identification
This paper presents an end-to-end system to identify writers in medieval manuscripts. The
proposed system consists in a three-step model for detection and classification of lines in the …
proposed system consists in a three-step model for detection and classification of lines in the …
A framework for analyzing financial behavior using machine learning classification of personality through handwriting analysis
Rigorous documentation and inspection methods are used by financial institutions to
manage the risk due to information asymmetry and moral hazard. Nevertheless, the intent of …
manage the risk due to information asymmetry and moral hazard. Nevertheless, the intent of …
Convolutional neural network and BLSTM for offline Arabic handwriting recognition
R Maalej, M Kherallah - 2018 International Arab conference on …, 2018 - ieeexplore.ieee.org
There have been an exciting advance in machine learning during the last decade. In fact,
increasing computer processing power has supported the analytical capabilities of …
increasing computer processing power has supported the analytical capabilities of …
Domain and writer adaptation of offline Arabic handwriting recognition using deep neural networks
Abstract Arabic Handwritten Text Recognition (AHTR) based on deep learning approaches
remains a challenging problem due to the inevitable domain shift like the variability among …
remains a challenging problem due to the inevitable domain shift like the variability among …