A collection of different scripts is employed in writing languages throughout the world.
Character and numeral recognition of a particular script is a key area in the field of pattern …

This paper comprehensively assesses the application of active learning strategies to
enhance natural language processing-based optical character recognition (OCR) models for …

In spite of various applications of digit, letter and word recognition, only a few studies have
dealt with Persian scripts. In this paper, deep neural networks are utilized through different …

Numerous archives and collections of past documents have become available recently
thanks to mass scale digitization and preservation efforts. Libraries, national archives, and …

Optical Character Recognition (OCR) is the process of identifying text in an image and
convert it into a digital form. Several approaches have been attempted to accurately …

Convolutional Recurrent Neural Network (CRNN) based architecture is an attractive branch
of Optical Character Recognition (OCR) studies. OCR is the process for transforming the …

Handwriting recognition principally entails optical character recognition. However, a
complete handwriting recognition system also handles formatting, performs correct …

Multi-modal document retrieval is designed to identify and retrieve various forms of multi-
modal content, such as figures, tables, charts, and layout information from extensive …

The Arabic handwritten character recognition is a research challenge due to the complexity
and variability of forms and writing styles of the Arabic alphabet. The current work focuses …

With the rapid development of mobile health, mechanisms for automatic data input are
becoming increasingly important for mobile health apps. In these apps, users are often …