Бакалавриат
2023/2024
Компьютерное зрение
Статус:
Курс по выбору (Прикладной анализ данных)
Направление:
01.03.02. Прикладная математика и информатика
Где читается:
Факультет компьютерных наук
Когда читается:
4-й курс, 3 модуль
Формат изучения:
без онлайн-курса
Охват аудитории:
для своего кампуса
Язык:
английский
Кредиты:
4
Контактные часы:
40
Course Syllabus
Abstract
The course is devoted to the main tasks and methods of computer vision, such as image processing and classification, image search by content, object selection and segmentation, image stylization, image synthesis, optical flow calculation, single and multiple target tracking, event recognition. To master the academic discipline, students must possess the knowledge and competencies of the following disciplines: Mathematical analysis; Linear algebra and geometry; Theory of Probability and Mathematical Statistics; Fundamentals and methodology of programming; Algorithms and data structures; Machine learning 1; Machine learning 2; Introduction to Deep Learning
Learning Objectives
- The main purpose of this course is to provide students with a comprehensive understanding of computer vision concepts, tools, and techniques, as well as practical experience through hands-on assignments. The course aims to equip students with the necessary skills and knowledge to excel in computer vision-related careers, such as machine learning, and prepare them for future research projects and job opportunities in the field.
Expected Learning Outcomes
- Understand various topics in computer vision, including image processing, feature extraction, object recognition, tracking, and autonomous driving.
- Gain practical experience through assignments such as panorama stitching, face recognition, and descriptors for image retrieval.
- Develop critical thinking and problem-solving skills through the coursework and discussions.
- Be prepared for future internships, research projects, and job opportunities in the field of computer vision.
- Understand transformers and multimodal computer vision concepts.
- Apply the knowledge and skills gained in the course to real-world computer vision applications.
Course Contents
- Object detectors
- Image segmentation
- Image conversion and generation
- Video Processing Basics
- Image Processing
- Feature Extraction
- Object Recognition
- Tracking
- Autonomous Driving
- Transformers
- Multimodal Computer Vision
- Assignments
- Problem-solving and Critical Thinking
- Real-world Applications
