Pattern Recognition (122 Computer Science)

Type: For the student's choice

Department: optoelectronics and information technologies

Curriculum

SemesterCreditsReporting
106Setoff

Lectures

SemesterAmount of hoursLecturerGroup(s)
1032Associate Professor Furgala Yu. M.ФеІм-13

Laboratory works

SemesterAmount of hoursGroupTeacher(s)
1032ФеІм-13Associate Professor Furgala Yu. M.

Опис навчальної дисципліни

The course is designed to provide students with theoretical knowledge of pattern recognition, methods of identifying key features, analyzing them, and assigning them to a specific class. The basis of the course is the consideration of mathematical models that provide the selection of image features, their classification, methods of analyzing the information received and making decisions on establishing correspondences, as well as the software implementation of recognition algorithms in various artificial intelligence systems.

The purpose of studying the discipline “Pattern Recognition” is to familiarize students with the theoretical foundations of solving the problem of pattern recognition, in particular, in images, and the goals are to develop practical skills that would allow them to effectively apply the acquired knowledge, algorithms, methods and available libraries and online resources to solve such problems.

Recommended Literature

Основна:

  • 1. M. Schlesinger, V. Hlavac Ten Lectures on Statistical and Structural Pattern Recognition // Computational Imaging and Vision, Vol. 24. Kluwer Academic Publishers – Dordrecht / Boston / London. – 2002. – 520 p.
  • 2. Муравський Л.І., Бобицький Я.В., Гаськевич Г.І. Оптичні інформаційні системи: Підручник. – Львів: СПОЛОМ, 2011. – 200 с.
  • 3. Русин Б.П. Структурно-лінгвістичні методи розпізнавання зображень в реальному часі. Київ, Наукова думка, 1986. – 128 с.
  • 4. Капустій Б.О., Русин Б.П., Таянов В.А. Системи розпізнавання образів з малими базами даних. Львів: СПОЛОМ, 2006, – 152 с

Додаткова:

  • 5. Evaluation of objects recognition effiency on mapes by various methods / Yuriy Furgala, Yuriy Mochulsky, Bohdan Rusyn // Data Stream Mining & Processing (DSMP 2018), IEEE Second International Conference. Lviv, Ukraine August 21-25, 2018, pp. 595-598
  • 6. Yu.Furgala, A.Velgosh, B.Rusyn, Yu.Korchak Proceedings of the Xth International Scientific and Practical Conference “Electronics and Information Technologies” (ELIT-2018), Lviv, Ukraine, August 30 – September 2, 2018, pp. A57-A60
  • 7. Ю.М.Фургала, А.С.Вельгош, С.Р.Вельгош, Б.П.Русин Використання гістограм кольору для ідентифікації об’єктів при масштабуванні та обертанні зображень, Електроніка та інформаційні технології, Т.13, – 2020, C.28-37
  • 8. A. Fesiuk, Y. Furgala. Keypoints on the images: comparison of detection by different methods. Електроніка та інформаційні технології. – 2023. – Вип. 21 – С. 15- 23.
  • 9. Yufei Bai. Research of image detection and matching algorithms. Proceedings of the 3rd International Conference on Signal Processing and Machine Learning. SPML2023, Chicago, USA, February 25-27, 2023, p.519-526

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