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Deep Learning in Computer Vision, Национальный исследовательский университет "Высшая школа экономики"

Оценки: 117
Рецензии: 29

Об этом курсе

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....

Лучшие рецензии

автор: SJ

Jun 12, 2018

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

автор: RR

Apr 19, 2019

Don't just read what's written on the projector. Try explaining it. And explain with code.

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Рецензии: 28

автор: Nabarun Dev

May 20, 2019

Worst course in the specialization.

автор: MASSON

May 15, 2019


-> Instructors read scripts during the whole course

-> No lecture slide (seriously ? thanks a lot for the effort)

-> Lectures are instructive even if you already know a bit about computer vision

-> Some topics and technical points are unclear, and quickly done with


-> ALL assignments are peer graded, meaning you never know if you will get a grade before deadline

-> Forums and discussions are deserted, you won't find any help there

-> Instructors provide very little explanations and directions

-> Some assignments can be pretty tough to complete if you are not strongly familiar with CV

-> Some assignments are unrelated to lectures (Week1 Alignment, Week5 GAN)

Overall the course is really interesting and instructive, but it feels like it was designed in a rush.

You can look elsewhere for a good course about computer vision.

автор: Jiachen Li

May 05, 2019

Course homework is actually not well designed for Coursera platform, some homework is not quite relevant to Deep Learning (i.e., HW1 and HW2) and some is very hard to complete (i.e., the last one, I tried on CPU for about 2 weeks). Also, the slides are not shared for this course in the series.

автор: Anmol Gupta

May 02, 2019

The content was good, but there are several drawbacks too

1 Content not explained well

2 Assignments had mistakes (like broken links, wrong descriptions)

3 Minimal or Non-Existing support from the staff.

автор: 杨伟

Apr 29, 2019

I am not sure how to rate this course exactly.

1, It is difficult to study. mainly because it just list most tech in computer vision but without detailed is not better than reading the origin papers.

2, Some quizz are very confusing, Actually adding a little explanation will make the quizz more clear.

3, The assignments are not uniform. it did not give a uniform environments. you need setup the env by yourself.

4, But when you finished the course, you will learn a lot things.

автор: William

Apr 22, 2019

The task is really practical and useful, but the courses content is too general and I hope for the future it could include some papers reading assignment

автор: Иванов Кирилл Сергеевич

Apr 20, 2019

This isn't a good course, difficult to understand and don't maintain by authors.

автор: Rachepalli Rajeev Reddy

Apr 19, 2019

Don't just read what's written on the projector. Try explaining it. And explain with code.

автор: Nandini

Apr 19, 2019

It was good

автор: Rohit Arya

Apr 13, 2019

The instructor is not explaining anything. Just reading off the slides. Given two stars only for assignments.