Pattern Recognition in Situation Awareness Systems

Major: System Analysis
Code of subject: 8.124.00.M.030
Credits: 3.00
Department: Information Systems and Networks
Lecturer: Yevhen Burov
Semester: 4 семестр
Mode of study: денна
Мета вивчення дисципліни: To form among young scientists system knowledge in the field of information technologies in the field of system analysis, to develop philosophical and linguistic competences, to form universal skills of a researcher, sufficient for the conduct and successful completion of scientific research and further professional and scientific activities for the construction of systems with situational awareness.
Завдання: Possession of in-depth professional and professional knowledge and practical skills to solve the complex problem of system analysis - building systems with situational awareness. 2. The ability to demonstrate systematic knowledge of modern research methods in the field of system analysis of robotic systems. 3. The ability to demonstrate in-depth knowledge in the field of scientific research on pattern recognition in autonomous intelligent systems.
Learning outcomes: 1. Possession of in-depth professional knowledge and practical skills for recognition and classification in complex systems of any complexity, to solve specific tasks of designing means of recognition and classification in complex systems of different physical nature. 2. Understanding the principles and methods of recognition and classification in complex systems, the range of tasks that contribute to the further development of the effective use of information resources of decision-making systems.
Required prior and related subjects: The previous ones related and subsequent educational disciplines academic disciplines Fundamentals of systems theory Modeling, analysis and synthesis of the interaction of complex information systems Probability theory and mathematical statistics. Methods of analysis and optimization of complex systems Information technologies System analysis of multi-criteria processes of various nature
Summary of the subject: Within the scope of the discipline, the issues of defining systems with situational awareness, models of such systems, the JDL framework, the use of ontologies and logical derivation in systems with situational awareness are considered; use of pattern recognition methods in such systems; methods of classification and clustering; use of Bayesian theory in pattern recognition tasks; teaching systems with and without a teacher; methods of grouping; use of neural networks for pattern recognition; structural pattern recognition.
Опис: Main definitions and models of systems with situational awareness General characteristics of the problem of pattern recognition in systems with CO. Methods of classification and clustering Bayesian decision theory in recognition tasks Evaluation of parameters and training with a teacher Non-parametric methods Learning without a teacher and grouping Using neural networks for pattern recognition Structural pattern recognition
Assessment methods and criteria: Diagnostics of knowledge is carried out by evaluating the completed laboratory work and credit control (written component) in the form of test questions of three levels of difficulty.
Критерії оцінювання результатів навчання: - individual work - 20 - performance of laboratory tasks - 30
Recommended books: Базова 1. Заяць В.М., Камінський Р.М. Методи розпізнавання образів: Навчальний посібник. – Львів: Видавництво Національного університету «Львівська політехніка», 2004. – 176 с. 2. Горелик А. Л., Скрипкин В. А. Методы распознавания М.: Высшая школа, 1989. 3. Айзерман М.А., Браверман Э.М., Розоноэр Л.И. Метод потенциальных функций в теории обучения машин. - М.: Наука, 2004. - 384 с. 4. Погребенник В.Д. Системи розпізнавання образів / Навч. посібник. – Львів: СПОЛОМ, 2007. – 170 с. 5. Главач В., Шлезингер М.И. Десять лекций по статистическому и структурному распознаванию образов. К.: Наукова думка, 2004. 6. Фисенко В.Т., Фисенко Т.Ю., Компьютерная обработка и распознавание изображений: учеб. пособие. - СПб: СПбГУ ИТМО, 2008. – 192 с. 7. Журавлев Ю.И. Избранные научные труды. – М: Изд. Магистр, 1998. - 420 с.www.irtc.org.ua/image/Files/Schles/esh10_full.pdf. 8. Местецкий Л.М. Математические методы распознавания образов. (Курс лекций). ВмиК МГУ: Москва, 2004). 9. Фу К. Структурные методы в распознавании образов. - М.: Мир, 2005. - 144 с. 10. Лепский А.Е., Броневич А.Г. Математические методы распознавания образов: Курс лекций. – Таганрог: Изд-во ТТИ ЮФУ, 2009. – 155 с. Допоміжна 1. Кутковецький В.Я. Розпізнавання образів [Текст] : навч. посіб. / В. Я. Кутковецький; Миколаївський держ. гуманітарний ун-т ім. Петра Могили комплексу "Києво-Могилянська академія". - Миколаїв : Видавництво МДГУ ім. Петра Могили, 2003. - 196 с. 2. Фомин Я. А. Распознавание образов: теория и применения. – 2-е изд. – М.: ФАЗИС, 2012. – 429 с. 3. Форсайт Дэвид А., Понс Джин. Компьютерное зрение. Современный поход – М.: Вильямс, 2004. – 928 с. 4. Горелик А. Л., Скрипкин В. А. Методы распознавания. — 4-е изд. — М.: Высшая школа, 1984, 5. Мандель И.Д. Кластерный анализ. – М.: Финансы и статистика. 1988. – 176 с. 6. Генкин В.Л. Системы распознавания автоматизированных производств / Генкин В.Л.; Ерош И.Л.; Москалев Э.С. – Л. : Машиностроение, 1988 . – 244с. 7. Чабан Л.Н. Теория и алгоритмы распознавания образов. Учебное пособие. М.: МИИГАиК. 2004. – 70с. 8. Мазуров В.Д. Математические методы распознавания образов. Уч. пособ. 2-е изд., доп. и перераб. - Екатеринбург: Изд-во Урал, ун-та, 2010.-101 с.