By the end of this course, learners will understand what computer vision is, as well as its mission of making computers see and interpret the world as humans do, by learning core concepts of the field and receiving an introduction to human vision capabilities. They are equipped to identify some key application areas of computer vision and understand the digital imaging process. The course covers crucial elements that enable computer vision: digital signal processing, neuroscience and artificial intelligence. Topics include color, light and image formation; early, mid- and high-level vision; and mathematics essential for computer vision. Learners will be able to apply mathematical techniques to complete computer vision tasks.
제공자:

Computer Vision Basics
뉴욕주립대학교 버펄로 캠퍼스이 강좌에 대하여
학습자 경력 결과
43%
25%
Basic programming skills & experience; familiarity with basic linear algebra, calculus & probability, and 3D co-ordinate systems & transformations
배울 내용
Understand what computer vision is and its goals
Identify some of the key application areas of computer vision
Understand the digital imaging process
Apply mathematical techniques to complete computer vision tasks
귀하가 습득할 기술
학습자 경력 결과
43%
25%
Basic programming skills & experience; familiarity with basic linear algebra, calculus & probability, and 3D co-ordinate systems & transformations
제공자:

뉴욕주립대학교 버펄로 캠퍼스
The University at Buffalo (UB) is a premier, research-intensive public university and the largest, most comprehensive institution of the State University of New York (SUNY) system. UB offers more than 100 undergraduate degrees and nearly 300 graduate and professional programs.

뉴욕주립대학교
The State University of New York, with 64 unique institutions, is the largest comprehensive system of higher education in the United States. Educating nearly 468,000 students in more than 7,500 degree and certificate programs both on campus and online, SUNY has nearly 3 million alumni around the globe.
강의 계획 - 이 강좌에서 배울 내용
Computer Vision Overview
In this module, we will discuss what computer vision is, the fields related to it, the history and key milestones of it, and some of its applications.
Color, Light, & Image Formation
In this module, we will discuss color, light sources, pinhole and digital cameras, and image formation.
Low-, Mid- & High-Level Vision
In this module, we will discuss the three-level paradigm of computer vision that was proposed by David Marr. We will also discuss low, mid, and high level vision.
Mathematics for Computer Vision
In this lecture, we will discuss the Mathematics used in Computer Vision, which includes linear algebra, calculus, probability, and much more.
검토
COMPUTER VISION BASICS의 최상위 리뷰
i really liked the course, but i wish that they would also help learn the programming in MATLAB a little, needs one extra week for the programming. Had to use external tools to learn the programming.
It is a good introduction course but I think some more demo coding for matlab in the first assignments will be a good thing so we don´t have to spend a lot of time on google and on trial and error.
Course was great ! And explained well but Matlab was not explained well. It's hard to complete week-4 assignment if you are not good at Matlab. Please provide python language for solving problems.
The course is fine, but it's too fundamental. Overall, it is more suit to personal who already had the fundamental in image processing knowledge. Else the course is a but higher level for others.
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