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Отзывы учащихся о курсе Computer Vision Basics от партнера Университет штата Нью-Йорк в Баффало

4.2
звезд
Оценки: 1,749

О курсе

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. This course is ideal for anyone curious about or interested in exploring the concepts of computer vision. It is also useful for those who desire a refresher course in mathematical concepts of computer vision. Learners should have basic programming skills and experience (understanding of for loops, if/else statements), specifically in MATLAB (Mathworks provides the basics here: https://www.mathworks.com/learn/tutorials/matlab-onramp.html). Learners should also be familiar with the following: basic linear algebra (matrix vector operations and notation), 3D co-ordinate systems and transformations, basic calculus (derivatives and integration) and basic probability (random variables). Material includes online lectures, videos, demos, hands-on exercises, project work, readings and discussions. Learners gain experience writing computer vision programs through online labs using MATLAB* and supporting toolboxes. * A free license to install MATLAB for the duration of the course is available from MathWorks....

Лучшие рецензии

AO

28 апр. 2020 г.

Lays a good foundation for Computer Vision. There should be more programming examples as some of the labs were beyond the scope of what was taught in the videos, especially the last one.

ZL

15 июля 2020 г.

I enjoyed learning about Computer Vision . The course showed me a new horizon and motivate me to discover this filed more. Thank you to All the professors ,and thank you Coursera!

Фильтр по:

26–50 из 495 отзывов о курсе Computer Vision Basics

автор: zehor l

16 июля 2020 г.

I enjoyed learning about Computer Vision . The course showed me a new horizon and motivate me to discover this filed more. Thank you to All the professors ,and thank you Coursera!

автор: Ali K M

15 июня 2019 г.

This course is a good course to start computer vision for beginner level student, and I offer This course to everyone who is eager to learn computer vision conceptually.

автор: Chayapol M

15 мая 2020 г.

Nice Course. I'm very hard to study and practice to passed the assignment. And that could give the experience on matlab including Image Processing skills. Thank a lot!

автор: Ewald H

22 мая 2020 г.

This was an excellent introduction to computer vision. I especially appreciated the various extra resources and in-depth explanations of how computer vision works.

автор: Dr A T

23 апр. 2020 г.

Very wonderful Experience . Got to learn so many new concepts starting from basics of Camera to the vast application area of CV. Very good coding assignments.

автор: Prithviraj V

5 июня 2020 г.

The basics of computer vision theory is well covered. The MATLAB exercises are bit tough but once you try them you can crack it.

автор: Abhishek K

8 апр. 2020 г.

it is a good starter for those guys who want to start learning computer vision for Robotics, AI, Image Processing, etc.

автор: i170368 H M

23 июля 2020 г.

Very informative course for beginner

автор: Kevin C

2 мая 2019 г.

Great Course

автор: Lida M

11 авг. 2019 г.

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.

автор: Rahul K D

10 мая 2020 г.

Definitely recommended for beginners. This course insight from concepts to application.

автор: SHETH D

8 авг. 2020 г.

Great course, but require higher understanding of MATLAB

автор: Dhruva G

15 апр. 2020 г.

As a complete beginner in image processing, I feel that more videos training the usage of MATLAB image processing functions should have been included rather than just giving assignments. A little more practical lectures other than theory would have been great.

Overall, I can definitely say I got a good idea about how human vision inspires computer vision and how much scope there is in this field in years to come.

автор: Anuj K

16 сент. 2020 г.

Prior knowledge of MATLAB is required which is not mentioned in the course description.

автор: Stefano F

26 дек. 2019 г.

Excercises seems to be a Matlab course, not computer vision

автор: Moulindu K

16 авг. 2020 г.

No similarity between lectures and assignments

автор: Alan T

29 окт. 2019 г.

Good information but a bit elementary.

автор: Syed S W

21 авг. 2019 г.

Not good enough, atleast for me. The assignments were totally, totally different from the stuff taught there. Plus everything taught here was a vague theory which was not even remotely related to the assignments. Expecting better quality in the next courses.

автор: Rishab K

22 дек. 2019 г.

The course definitely doesn't carry significant content and what after it.

after basics there should be some more courses for advance training.

The programming assignment were more than irrelevant.

sorry for the bad feedback.

but teaching was good

автор: Simun K

18 мая 2020 г.

Not enough resources to learn from. Videos are not explaining the curriculum that is tested in MatLab "graded external tool". Forum discussions are far more helpful than the videos itself.

автор: Josh E

14 апр. 2020 г.

The learning does not prepare you for the assignments and all assignments are either pre-solved or cannot be solved without a lot of trial and error, no logic.

автор: KSHITIJ B

12 мая 2020 г.

Not in depth knowledge provided , just gave overview of various topics in short videos , reading material is better than the videos provided.

автор: Göktuğ Y

7 мая 2020 г.

If you want to pass this course, you must really know how to use MATLAB!

автор: Saurav P

29 апр. 2020 г.

completely unrelated content and assignments

автор: Tanvi P

2 мая 2020 г.

My first bad experience with Coursera content. It pains me to write this review, because it is always difficult to criticise other academics. The video lecture content throughout this course is very generic, like what one might hear about computer vision in a TED talk or on TV.

One speaker's body language was very distracting, another's pronunciation is hard to catch and many slides are tackily animated, so I ended up reading the video transcripts instead of watching them. Most videos are 2 or 3 minutes long, and there aren't that many videos. It's almost as if somebody forgot to upload the rest of the lecture videos!

The videos mostly contain introductions, applications and information surveys about various aspects of computer vision, with kitten and puppy pictures thrown in as "examples" to keep you interested.

The student grapples with fairly complex programming assignments with no idea about where to begin. Each quiz contains only one qualitative Yes or No question, which was not related to the video.

Though the course teaches you almost nothing about computer vision algorithms, it does squeeze in a few interesting minutes about human vision and basic optics, but that is not what a student who signs up for this course expects to learn here.

The math section (one week's worth, out of four) is made up of four or five 1-minute videos about the importance of linear algebra and calculus, but there's not a single equation in sight. The supplementary material for the entire course consists of either Wikipedia pages or research papers that the lecture content does not prepare you to read and absorb.

Even if you are a more senior industry professional interested only in a top level understanding of computer vision without getting into the math of it, you won't be able to complete the course because the programming assignments require some serious math skills that the course does not cover.

All in all, not a recommended course for your time and money. If you are looking for some good learning, Andrew Ng's Machine Learning course here on Coursera is more interesting and useful for computer vision than this one!