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Deep Learning in Computer Vision, National Research University Higher School of Economics

82 calificaciones
15 revisiones

Acerca de este Curso

Deep learning added a huge boost to the already rapidly developing field of computer vision. With deep learning, a lot of new applications of computer vision techniques have been introduced and are now becoming parts of our everyday lives. These include face recognition and indexing, photo stylization or machine vision in self-driving cars. The goal of this course is to introduce students to computer vision, starting from basics and then turning to more modern deep learning models. We will cover both image and video recognition, including image classification and annotation, object recognition and image search, various object detection techniques, motion estimation, object tracking in video, human action recognition, and finally image stylization, editing and new image generation. In course project, students will learn how to build face recognition and manipulation system to understand the internal mechanics of this technology, probably the most renown and oftenly demonstrated in movies and TV-shows example of computer vision and AI....

Principales revisiones

por SJ

Jun 12, 2018

Excellent course! Quiz questions are conceptual and challenging and assignments are pretty rigorous and 100% practical application oriented.

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14 revisiones

por 李朝辉

Dec 14, 2018

the descriptions of homeworks are sometimes ambiguous, students may spend too much time trying to understand. Also, I strongly recommend teachers can interactive with the PPT when lecturing, instead of reading the draft directly.

por Jakub Bartczuk

Nov 23, 2018


-thorough course material

-ambitious and interesting assignments


-there isn't ANY assistance from the instructors or the TA. If you check TAs then you'll see that all of them written 0 posts on the forum.

-most assignments are severely underspecified. This makes them much harder than they should be, and it makes students spend hours on minutiae of preprocessing instead of more important stuff.


Nov 06, 2018

Lecturer had a difficult accent to understand. Briefly put up formulas and graphs but didn't explain them. No examples were worked through yet the quiz required this to be done. To understand this subject I will have to go away and study this from another source before I can understand it.

por Nafiseh Salmani Niyasar

Oct 30, 2018

Worst presentation ever! Hard to follow, he reads from a text with no explanation. The worst! I also have to read the transcript to understand what he is saying.

por Raymond Phan

Oct 02, 2018

Slides are not available, only the videos. Quiz questions are very unclear and ambiguous. Assignments have almost no direction and require many hours of commitment. Requires a significant amount of prior knowledge before taking this course. Would not recommend. Andrew Ng's specialization is much better.

por Kocić Ognjen

Sep 20, 2018


- excellent and challenging exercises

- relevant topics


- poor feedback and course management

- lectures that do not teach you anything, it is more a taxonomy of what exists out there than explanation of anything

por Matt Vowels

Sep 10, 2018

Some good topics and interesting homeworks, however, the lectures are rushed through without much explanation or examples, and there are many frustrating mistakes that belie the fact that this course is apparently not maintained and there is no support for students on the forums. Could be really good, but it's not there yet.

por Wei Xie

Aug 31, 2018

Nice introductory course. It include many background knowledge of computer vision before deeplearning and is important to know.

por Потапчук Антон Алексеевич

Aug 04, 2018

Lectures are good (mostly). But home assignments are very bad. Some links for datasets are broken. Admins did not fix it after a month (I found a message about it on the forum)!!! There are a lot of mistakes in a code. So, I spent a huge amount of time just for fixing bugs. It was very painful.

I think, administrators should read comments sometimes and update repos.

Some home assignments are very cool. But, mostly it is not possible to run it on a low-class laptop.

Moreover, there are a lot of mistakes in quizzes that was not fixed for a long time! So, people tried a grid search for answers. I definetely recommend to administration start fixing this bugs. This course is very good, but all this bugs discourage any desire to pass it.

por Rohan Khollamkar

Jul 24, 2018

Very poor instructions in course, can' even understand a thing.

1.Tutor does not explain clearly what exactly is happening, just reads the formula on screen as it is.

2.What is kernel and why we use it. Also what happens exactly when we convolutionalize,image matrix. Nothingggg is explained.

3. How one should solve the maths in graded assignments, when can't even understand the math behind the technique.

4. Speaking accent of tutor is very bad, can't understand if captions are not enabled.

I have taken many courses on coursera, which were very informative and in-depth explanation, but this course is just like National research university has nothing to do with if students are actually learning or not. It is more like earning money only.

There are several other cons which I have not mentioned.Very very disappointed.