Stanislav Protasov

Stanislav Protasov
Innopolis University · Machine learning and knowledge representation laboratory

PhD

About

30
Publications
7,118
Reads
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181
Citations
Introduction
With my students I work on applications of machine learning to various tasks: medical image analysis, social networks analysis, recommendations. My personal interest today lay in the area of applied quantum programming. I work on methods and algorithms which make use of NISQ systems.
Additional affiliations
June 2015 - May 2016
Innopolis University
Position
  • PostDoc Position
Education
September 2004 - August 2012
Voronezh State University
Field of study
  • Computer Science

Publications

Publications (30)
Article
Full-text available
Quantum processing units (QPU) in theory propose a computational supremacy in a significant number of tasks. Quantum programs are well suited for vector and matrix data processing. The greatest concern is whether physical implementations will step over the noise and decoherence limitations: today in the noisy intermediate-scale quantum (NISQ) era t...
Conference Paper
Full-text available
Medical imaging is a useful tool that simplifies the diagnosing and treatment. Having high-quality images doctor can make a statement about disease and correct the further recovery steps. The image quality depends on such factors as equipment condition, scanning correctness and patient's body structure. The solid inclusions inside the human body ca...
Conference Paper
Full-text available
Contemporary quantum algorithms, being efficient theoretically, fail to run on real QPUs. One reason for these failures is the algorithm's probabilistic nature, which is amplified by imperfections in hardware implementation. Grover search is such a probabilistic method, which enables other methods in quantum optimization and machine learning. In th...
Conference Paper
Full-text available
Large multidimensional data sets are hard to visualize. Most existing methods dedicate visual space to multiple items or multiple features. In this work, we explore dimensionality reduction methods to capture both properties. We show that self-organizing maps (SOM) are the good choice for screen and paper visualization. We involve colors to make mu...
Preprint
Full-text available
Researchers have put a lot of effort into reducing the gap between current QPU capabilities and potential supremacy. One practical approach is to unload, at least partially, computations from quantum computers to the CPU. Arbitrary quantum state initialization is an example of such computations. The known algorithms are exponentially complex if cou...
Preprint
Full-text available
One of the crucial tasks in computer science is the processing time reduction of various data types, i.e., images, which is important for different fields-from medicine and logistics to virtual shopping. Compared to classical computers, quantum computers are capable of parallel data processing, which reduces the data processing time. This quality o...
Experiment Findings
Full-text available
In this paper we reproduce theoretical Buffon needle experiment. We run 7 separate tests with different initial parameters. We numerically assess solution accuracy and method convergence and provide suggestions for future experiments in this area. The obtained approximation is π = 3.07505 ± 1.31692 and it does not contradict original hypothesis.
Preprint
Quantum processing units (QPU) in theory propose a computational supremacy in a significant number of tasks. Quantum programs are well suited for vector and matrix data processing. The greatest concern is whether physical implementations will step over the noise and decoherence limitations: today in the NISQ (noisy intermediate-scale quantum) era t...
Preprint
Full-text available
Quantum programs allow to process multiple bits of information simultaneously, which is useful in multidimensional data handling. Images are an example of such multidimensional data. Our work reviews 15 quantum image encoding works and compares 8 of them by 3 metrics: number of utilized qubits, quantum circuit depth, and quantum volume. Our work in...
Preprint
Full-text available
Contemporary quantum algorithms, being efficient theoretically, fail to execute on real QPUs. One reason for these failures is the algorithm's probabilistic nature, which is amplified by hardware implementation imperfections. Grover search is such a probabilistic method, which enables other methods in quantum optimization and machine learning. In t...
Article
Full-text available
K-nearest neighbours (kNN) is a very popular instance-based classifier due to its simplicity and good empirical performance. However, large-scale datasets are a big problem for building fast and compact neighbourhood-based classifiers. This work presents the design and implementation of a classification algorithm with index data structures, which w...
Preprint
Full-text available
We present an approach to fully automatic metal artifact detection in the computed tomography (CT) studies. Artifacts are parts of the image that corrupt information. Our technique localizes artifacts as the first step of the artifact removal algorithm. Artifacts appear in CT images as 3D connected components. We segment the artifact's area as a co...
Preprint
Full-text available
K-nearest neighbours (kNN) is a very popular instance-based classifier due to its simplicity and excellent empirical performance. However, large-scale datasets are a big problem for building fast and compact neighbourhood-based classifiers. This work targets the design and implementation a classification algorithm to be used with efficient data str...
Conference Paper
Full-text available
With exponential data growth search engines require more memory for storage and time for search. The data is indexed to increase search speed, which requires additional memory. In this study we develop a fully functional search engine for Wikipedia articles and compare different indexing techniques. Using vector quantization for compression we fit...
Conference Paper
Full-text available
Big problem visualization at a single plot can be considered as a handy tool for making managerial decisions. Thesaurus can be used to represent important properties of a large text corpus. In this work I propose fully automatic method of visualizing text dataset thesaurus on a plain graph which can be used for domain exploration. Resulting visuali...
Conference Paper
Full-text available
Метод k ближайших соседей (kNN) обязывает хранить всю обучающую выборку, что ограничивает его применимость. В работе рассматривается подход, позволяющий уменьшить размер хранимых данных, а также увеличить устойчивость решения на границе классов за счёт процедуры голосования, учитывающей пересечение границы. Метод превосходит оригинальный алгоритм п...
Conference Paper
Full-text available
В работе представлен однопроходный детектор связных объектов, использующий модифицированую структуру union-find. Предложенные модификации позволяют за константное время осуществлять слияние компонент и таким образом достигать линейного времени работы алгоритма в зависимости от площади изображения.
Article
Full-text available
The semantic video indexing problem is still underexplored. Solutions to the problem will significantly enrich the experience of video search, monitoring, and surveillance. This paper concerns scene detection and annotation, and specifically, the task of video structure mining for video indexing using deep features. The paper proposes and implement...
Article
Full-text available
Hyperspectral image classification with a limited number of training samples without loss of accuracy is desirable, as collecting such data is often expensive and time-consuming. However, classifiers trained with limited samples usually end up with a large generalization error. To overcome the said problem, we propose a fuzziness-based active learn...
Data
The Indian Pines (corrected) dataset, consisting of 145*145 samples and 220 spectral bands with a spatial resolution of 20 m and a spectral range of 0.4–2.5 μm. Twenty noisy bands were removed prior to the analysis, whereas the remaining 200 bands were used in our experimental setup. The removed bands are 104–108, 150–163, and 220. The original In...
Data
This file contains MATLAB code for reshaping and rewriting of the original Indian Pines dataset and ground truths into text files as per journal requirements. (M)
Data
The original Indian Pines ground truths consist of 16 classes. The ground truth classes and the number of samples per class (class name-number of samples) are as follows: ““Alfalfa-46”, “Corn Notill-1428”, “Corn-Mintel-830”, “Corn-237”, “Grass Pasture-483”, “Grass Trees-730”, “Grass Pasture Mowed-28”, “Hay Windrowed-478”, “Oats-20”, “Soybean Notill...
Article
Full-text available
Automatic analysis of the video is one of most complex problems in the fields of computer vision and machine learning. A significant part of this research deals with (human) activity recognition (HAR) since humans, and the activities that they perform, generate most of the video semantics. Video-based HAR has applications in various domains, but on...
Article
Full-text available
Hyperspectral image analysis often requires selecting the most informative bands instead of processing the whole data without losing the key information. Existing band reduction (BR) methods have the capability to reveal the nonlinear properties exhibited in the data but at the expense of loosing its original representation. To cope with the said i...
Article
Full-text available
Автоматизация контроля успеваемости студентов является важной задачей для повышения производительности преподавателей и управляемости учебного процесса. При этом необходимо всесторонне анализировать результаты автоматизации, выявлять как позитивные, так и негативные итоги. В нашей работе мы рассматриваем результаты внедрения системы управления обуч...
Conference Paper
Full-text available
Smartphones have ubiquitously integrated into our home and work environments. It is now a common practice for people to store their sensitive and confidential information on their phones. This has made it extremely important to authenticate legitimate users of a phone and block imposters. In this paper, we demonstrate that the motion dynamics of sm...
Article
Full-text available
1]. Большинство существующих алгоритмов стерео-сопоставления может быть разбито на две категории решений: локальную и глобальную. Вообще говоря, локальные алгоритмы являются с точки зрения вычислений менее затратными, а глобальные алгоритмы формируют более точные ДД. Задачу построения сеточной модели по множеству точек в трёхмерном пространстве мож...

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Projects

Projects (5)
Project
This project targets the idea, that visualizing a big text dataset can bring additional value in terms of exploration and making decisions. We build visual tools to explore large text datasets.