Urdu Nastaliq recognition using convolutional–recursive deep learning
Recent developments in recognition of cursive scripts rely on implicit feature extraction
methods that provide better results as compared to traditional hand-crafted feature extraction …
methods that provide better results as compared to traditional hand-crafted feature extraction …
Cutting the error by half: Investigation of very deep cnn and advanced training strategies for document image classification
We present an exhaustive investigation of recent Deep Learning architectures, algorithms,
and strategies for the task of document image classification to finally reduce the error by …
and strategies for the task of document image classification to finally reduce the error by …
Efficient skew detection and correction in scanned document images through clustering of probabilistic hough transforms
Documents scanning is still one of the widely used documents digitization steps; however,
skew in scanned documents is inevitable. If this skew is not corrected, the extraction of …
skew in scanned documents is inevitable. If this skew is not corrected, the extraction of …
Urdu Nasta'liq text recognition using implicit segmentation based on multi-dimensional long short term memory neural networks
The recognition of Arabic script and its derivatives such as Urdu, Persian, Pashto etc. is a
difficult task due to complexity of this script. Particularly, Urdu text recognition is more difficult …
difficult task due to complexity of this script. Particularly, Urdu text recognition is more difficult …
Cascade network with deformable composite backbone for formula detection in scanned document images
This paper presents a novel architecture for detecting mathematical formulas in document
images, which is an important step for reliable information extraction in several domains …
images, which is an important step for reliable information extraction in several domains …
Kpti: Katib's pashto text imagebase and deep learning benchmark
This paper presents the first Pashto text image database for scientific research and thereby
the first dataset with complete handwritten and printed text line images which ultimately …
the first dataset with complete handwritten and printed text line images which ultimately …
Benchmark Pashto handwritten character dataset and Pashto object character recognition (OCR) using deep neural network with rule activation function
In the area of machine learning, different techniques are used to train machines and perform
different tasks like computer vision, data analysis, natural language processing, and speech …
different tasks like computer vision, data analysis, natural language processing, and speech …
Persian Optical Character Recognition Using Deep Bidirectional Long Short-Term Memory
Optical Character Recognition (OCR) is a system of converting images, including text, into
editable text and is applied to various languages such as English, Arabic, and Persian …
editable text and is applied to various languages such as English, Arabic, and Persian …
Recognizing challenging handwritten annotations with fully convolutional networks
A Kölsch, A Mishra, S Varshneya… - … on Frontiers in …, 2018 - ieeexplore.ieee.org
This paper introduces a very challenging dataset of historic German documents and
evaluates Fully Convolutional Neural Network (FCNN) based methods to locate handwritten …
evaluates Fully Convolutional Neural Network (FCNN) based methods to locate handwritten …
OCR with the Deep CNN Model for Ligature Script‐Based Languages like Manchu
D Zhang, Y Liu, Z Wang, D Wang - Scientific programming, 2021 - Wiley Online Library
Manchu is a low‐resource language that is rarely involved in text recognition technology.
Because of the combination of typefaces, ordinary text recognition practice requires …
Because of the combination of typefaces, ordinary text recognition practice requires …