Neural networks for document image preprocessing: state of the art
Neural network are most popular in the research community due to its generalization
abilities. Additionally, it has been successfully implemented in biometrics, features selection …
abilities. Additionally, it has been successfully implemented in biometrics, features selection …
Recognition of Urdu handwritten characters using convolutional neural network
In the area of pattern recognition and pattern matching, the methods based on deep learning
models have recently attracted several researchers by achieving magnificent performance …
models have recently attracted several researchers by achieving magnificent performance …
Distinction between handwritten and machine-printed text based on the bag of visual words model
In a variety of documents, ranging from forms to archive documents and books with
annotations, machine printed and handwritten text may coexist in the same document …
annotations, machine printed and handwritten text may coexist in the same document …
Meta‐feature based few‐shot Siamese learning for Urdu optical character recognition
Standard convolution neural network (CNN) achieves high level of accuracy for the
recognition of characters in different languages. However, like other deep neural networks …
recognition of characters in different languages. However, like other deep neural networks …
Automatic discrimination between printed and handwritten text in documents
Recognition techniques for printed and handwritten text in scanned documents are
significantly different. In this paper we address the problem of identifying each type. We can …
significantly different. In this paper we address the problem of identifying each type. We can …
Signature segmentation from document images
In this paper we propose a novel method for the extraction of signatures from document
images. Instead of using a human defined set of features a part-based feature extraction …
images. Instead of using a human defined set of features a part-based feature extraction …
A system for handwritten and printed text classification
BM Garlapati, SR Chalamala - 2017 UKSim-AMSS 19th …, 2017 - ieeexplore.ieee.org
An optical character recognition (OCR) system recognizes either printed or handwritten text.
Hence it is required to seperate machine printed text from handwritten text in scanned …
Hence it is required to seperate machine printed text from handwritten text in scanned …
Identification of machine-printed and handwritten words in Arabic and Latin scripts
A Saïdani, AK Echi, A Belaid - 2013 12th International …, 2013 - ieeexplore.ieee.org
Our ultimate objective is to contribute to the field of script and nature identification to be able
to differentiate, at word level, handwritten or machine-printed, Arabic and Latin scripts …
to differentiate, at word level, handwritten or machine-printed, Arabic and Latin scripts …
The effects of varying population density in a fine-grained parallel genetic algorithm
This paper introduces a new method for controlling selection pressure in fine-grained
parallel GAs. Our model, inspired by percolation theory, employs a" seeding" mechanism …
parallel GAs. Our model, inspired by percolation theory, employs a" seeding" mechanism …
Hybrid HMM/BLSTM system for multi-script keyword spotting in printed and handwritten documents with identification stage
In this paper, we propose a novel script-independent approach for word spotting in printed
and handwritten multi-script documents. Since each writing type and script need to be …
and handwritten multi-script documents. Since each writing type and script need to be …