In this paper, we introduce an “on the device” text line recognition framework that is
designed for mobile or embedded systems. We consider per-character segmentation as a …

Automatic optical recognition of documents is a traditional function of modern document
processing systems. In this context, recognition represents a complex process which …

In this paper we study the real-time augmentation-method of increasing variability of training
dataset during the learning process. We consider the most common label-preserving …

In this paper, we study the problem of feature points description in the context of document
analysis and template matching. Our study shows that specific training data is required for …

For text line recognition, much attention is paid to augmentation of the training images. Yet
the inner structure of the textual information in the images also affects the accuracy of the …

Despite the significant success in the field of text recognition, complex and unsolved
problems still exist in this field. In recent years, the recognition accuracy of the English …

In this paper, we consider the problem of detecting counterfeit identity documents in images
captured with smartphones. As the number of documents contain special fonts, we study the …

Nowadays, the accessibility of digitized historical documents is extremely important to
facilitate fast and efficient retrieval of historical information and knowledge extraction from …

In this work, we present the auto-clustering method which can be used for pattern
recognition tasks and applied to the training of a metric convolutional neural network. The …

This research addresses a critical challenge in the field of generative models, particularly in
the generation and evaluation of synthetic images. Given the inherent complexity of …