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Deep Learning in Computer Vision

Higher School of Economics via Coursera

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  • Provider Coursera
  • Subject Deep Learning
  • $ Cost Free Online Course (Audit)
  • Session Upcoming
  • Language English
  • Certificate Paid Certificate Available
  • Start Date
  • Duration 5 weeks long

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Overview

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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.

Taught by

Anton Konushin and Alexey Artemov

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Reviews for Coursera's Deep Learning in Computer Vision
3.0 Based on 2 reviews

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Anonymous
4.0 5 months ago
Anonymous completed this course.
Techniques discussed in the course are state of the art and are presented in a very engaging manner. The highlight of the course are the assignments which, unlike many courses I've seen, give a lot of freedom as per coding methodology. You'll implement basic edge detectors from scratch, perform image correction, keypoints regression, face detection and recognition and you'll also implement image generation!
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Jakub B
2.0 2 weeks ago
Jakub completed this course, spending 6 hours a week on it and found the course difficulty to be very hard.
Pros:

-thorough course material

-course teaches older methods in addition to deep learning - most CV with DL courses don't do that

-ambitious and interesting assignments

Cons:

-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.

-there are lots of bugs. For example in week 4 slides are bugged exactly in the part relevant to one quiz problem. Assignments also contain bugs.

-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.

Overall the course has great content, but it's hardly finished. The bugs wouldn't be so annoying if they wouldn't make finishing the course much harder.
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