The flourishing blossom of deep learning has witnessed the rapid development of text
recognition in recent years. However, the existing text recognition methods are mainly …

Many studies on (Offline) Handwritten Text Recognition (HTR) systems have focused on
building state-of-the-art models for line recognition on small corpora. However, adding HTR …

Online and offline handwritten Chinese text recognition (HTCR) has been studied for
decades. Early methods adopted oversegmentation-based strategies but suffered from low …

The advent of convolutional neural networks (CNNs) has accelerated the progress of
computer vision from many aspects. However, the majority of the existing CNNs heavily rely …

In recent years, deep learning models (eg Convolutional Neural Networks (CNN) and Long
Short-Term Memories (LSTM)), have been successfully applied to text sentiment analysis …

Abstract Scene Text Image Super-resolution (STISR) aims to recover high-resolution (HR)
scene text images with visually pleasant and readable text content from the given low …

There are many researchers working on handwritten text recognition (HTR) and also
contributing to HTR domain. Even though many research methods are existing for HTR …

Integrated convolutional neural network (CNN) and deep bidirectional long short-term
memory (DBLSTM) based character models have achieved excellent recognition accuracies …

With continuous development of artificial intelligence, text classification has gradually
changed from a knowledge-based method to a method based on statistics and machine …

Generative adversarial networks (GANs) have proven hugely successful in variety of
applications of image processing. However, generative adversarial networks for handwriting …