About this Course

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Coursera Labs
Includes hands on learning projects.
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Advanced Level

This is an advanced course, intended for learners with a background in computer vision and deep learning.

Approx. 31 hours to complete
English

What you will learn

  • Work with the pinhole camera model, and perform intrinsic and extrinsic camera calibration

  • Detect, describe and match image features and design your own convolutional neural networks

  • Apply these methods to visual odometry, object detection and tracking

  • Apply semantic segmentation for drivable surface estimation

Flexible deadlines
Reset deadlines in accordance to your schedule.
Shareable Certificate
Earn a Certificate upon completion
100% online
Start instantly and learn at your own schedule.
Coursera Labs
Includes hands on learning projects.
Learn more about Coursera Labs External Link
Advanced Level

This is an advanced course, intended for learners with a background in computer vision and deep learning.

Approx. 31 hours to complete
English

Offered by

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University of Toronto

Syllabus - What you will learn from this course

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Week1
Week 1
2 hours to complete

Welcome to Course 3: Visual Perception for Self-Driving Cars

2 hours to complete
4 videos (Total 18 min), 4 readings
7 hours to complete

Module 1: Basics of 3D Computer Vision

7 hours to complete
6 videos (Total 43 min), 4 readings, 2 quizzes
Week2
Week 2
7 hours to complete

Module 2: Visual Features - Detection, Description and Matching

7 hours to complete
6 videos (Total 44 min), 5 readings, 1 quiz
Week3
Week 3
3 hours to complete

Module 3: Feedforward Neural Networks

3 hours to complete
6 videos (Total 58 min), 6 readings, 1 quiz
Week4
Week 4
3 hours to complete

Module 4: 2D Object Detection

3 hours to complete
4 videos (Total 52 min), 4 readings, 1 quiz

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About the Self-Driving Cars Specialization

Self-Driving Cars

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