One of the challenges in recognizing handwritten texts is the individual style of writing. There
is the structural similarity of the different digits to each other in writing. Along with the …

Given the prevalence of handwritten documents in human interactions, optical character
recognition (OCR) for documents holds immense practical value. OCR is a field that …

An electric grid consists of transformers, generation centers, communication links, control
stations, and distributors. Collectively these components help in moving power from one …

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 …

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 …

Efficient spectrum utilization is a prominent issue in cognitive radio networks. Owing to this,
power allocation policies are proposed which underlay cognitive radio networks together …

Deep learning models are considered a revolutionary learning paradigm in artificial
intelligence and machine learning, piquing the interest of image recognition and computer …

Abstract Arabic Handwriting Recognition (AHR) is a complex task involving the
transformation of handwritten Arabic text from image format into machine-readable data …

Abstract Convolutional Neural Networks (CNNs) show state-of-the-art performance in
handwritten word recognition. Existing CNNs operate on one language and their accuracy …

Recognition of handwritten digits is a stimulating task in recent years. Even though many
deep learning-oriented classification algorithms are deliberated for handwritten digit …