Olga Radyvonenko

• PhD
• Head of Department at Samsung

Legible handwriting refers to the written work that can be easily read and comprehended by both the writer and other people. Despite significant progress in the field of digital handwriting processing, enhancing the visual quality of handwritten content remains a relatively unexplored and challenging task. In this paper, we propose and analyze two...

Advances in the development of devices with handwritten input, and the emergence of deep learning have led to the rapid development of handwriting recognition applications, but the methods and implications of handwritten interaction on the Lock Screen of the smartphone, taking into account usability, are still not sufficiently considered in existin...

The modern recognition methods based on deep learning have established high requirements for the size of training data. However, such data is not always publicly available, often undersized, or limited by the number of classes. Preparing ground truth data is very expensive, time-consuming, and error-prone during collecting as well as annotation for...

Stroke classification is an essential task for applications with free-form handwriting input. Implementation of this type of application for mobile devices places stringent requirements on different aspects of embedded machine learning models, which results in finding a trade-off between model performance and model complexity. In this work, a novel...

An electronic device for converting a handwriting input to text and a method of operating the same. The method includes obtaining information about a handwriting input, recognizing at least one character corresponding to the handwriting input, obtaining a character sequence in which the at least one character is arranged in order and geometry infor...

The paper presents an original solution to the online handwritten document processing in a free form, which is aimed at separating multi-class handwritten documents into texts, tables, formulas, drawings, etc. Stroke classification is an important step in automatic document layout analysis (DLA) in handwritten document recognition systems. Major DL...

Handwritten mathematical expressions are an essential part of many domains, including education, engineering, and science. The pervasive availability of computationally powerful touch-screen devices, similar to the recent emergence of deep neural networks as high-quality sequence recognition models, result in the widespread adoption of online recog...

A system and method for detecting, identifying, and displaying handwriting-based entry is provided. The system and method include features for detecting entry of at least one first letter based on handwriting, identifying a style of the at least one first letter, and displaying at least one second letter associated with the at least one first lette...

Advances in deep learning end-to-end recognition systems allow moving forward intelligent user interfaces. At the same time, they lead to new implications and restrictions in the UI design. In this paper, we discuss new requirements for the pen-centric intelligent user interface for operating with mathematical expressions. We argue that the followi...

Text-based interaction with the use of mobile devices is now ubiquitous, its main outlets being social networks, messengers, email conversations, virtual assistants, accessibility applications, etc. Its status implies the need to facilitate text input by the user and to devise ways to provide verbal feedback. In this paper, we discuss a method of u...

The use of the minimalistic design in the document editing UI based on novel handwriting recognition technologies for mobile devices with a touch screen is very limited in real-world applications, mainly due to the propagation of errors made by recognition engines for different types of input. It is caused by the iterative nature of recognition for...

In this work, a solution for handwriting text extraction from images with visual user assistance is proposed. Use of end-to-end systems that pipe together text detection and recognition is often awkward because the user cannot influence the detection stage. On the other hand, glossing over the word's regions to help system with text localization re...

(EN) An electronic device is disclosed. The electronic device comprises: a storage unit for storing a training model of a multi-dimensional long short-term memory (MDLSTM); and a processor for acquiring an image including at least one of handwritten text and printed text, identifying each text line region in the image through image processing, and...

In this work, the approach for online recognition of 2D sequences using deep bidirectional LSTM was proposed. One of the complex cases of online sequence recognition is handwritten mathematical expressions (HME). In spite of many achievements in this area, it is a still challenging task as, in addition to character segmentation and recognition, the...

This paper is dedicated to classification of hand-written/drawn input made on screen of mobile devices into two classes: Text and Non-Text. A deep-learning solution using gated recurrent and feed-forward artificial neural networks has been proposed. Two approaches have been compared: a real-time approach, designed to process data at input time with...

An efficient algorithm for recurrent neural network training is presented. The approach increases the training speed for tasks where a length of the input sequence may vary significantly. The proposed approach is based on the optimal batch bucketing by input sequence length and data parallelization on multiple graphical processing units. The baseli...

The paper provides a practical solution to a real-time text/shape differentiation problem for online handwriting input. The proposed structure of the classification system comprises stroke grouping and stroke classification blocks. A new set of features is derived that has low computational complexity. The method achieves 98.5 % text/shape classifi...

An efficient algorithm for recurrent neural network training is presented. The approach increases the training speed for tasks where a length of the input sequence may vary significantly. The proposed approach is based on the optimal batch bucketing by input sequence length and data parallelization on multiple graphical processing units. The baseli...

In this paper the model to study risk factors for hepatitis B and to identify the main causes affecting the incidence of hepatitis B was developed. Proposed model allows to identify the dependencies between the risk factors and the hepatitis B morbidity, detect major factors that affect the intensity of the epidemic process and verify the effective...