课程信息
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第 3 门课程(共 4 门)

100% 在线

立即开始,按照自己的计划学习。

可灵活调整截止日期

根据您的日程表重置截止日期。

高级

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

完成时间大约为20 小时

建议:6 weeks of study, 5-6 hours per week...

英语(English)

字幕:英语(English)

您将学到的内容有

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

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

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    Apply these methods to visual odometry, object detection and tracking

  • Check

    Apply semantic segmentation for drivable surface estimation

第 3 门课程(共 4 门)

100% 在线

立即开始,按照自己的计划学习。

可灵活调整截止日期

根据您的日程表重置截止日期。

高级

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

完成时间大约为20 小时

建议:6 weeks of study, 5-6 hours per week...

英语(English)

字幕:英语(English)

教学大纲 - 您将从这门课程中学到什么

1
完成时间为 2 小时

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

4 个视频 (总计 18 分钟), 4 个阅读材料
4 个视频
Welcome to the course4分钟
Meet the Instructor, Steven Waslander5分钟
Meet the Instructor, Jonathan Kelly2分钟
4 个阅读材料
Course Prerequisites15分钟
How to Use Discussion Forums15分钟
How to Use Supplementary Readings in This Course15分钟
Recommended Textbooks15分钟
完成时间为 7 小时

Module 1: Basics of 3D Computer Vision

6 个视频 (总计 43 分钟), 4 个阅读材料, 2 个测验
6 个视频
Lesson 1 Part 2: Camera Projective Geometry8分钟
Lesson 2: Camera Calibration7分钟
Lesson 3 Part 1: Visual Depth Perception - Stereopsis7分钟
Lesson 3 Part 2: Visual Depth Perception - Computing the Disparity5分钟
Lesson 4: Image Filtering7分钟
4 个阅读材料
Supplementary Reading: The Camera Sensor30分钟
Supplementary Reading: Camera Calibration15分钟
Supplementary Reading: Visual Depth Perception30分钟
Supplementary Reading: Image Filtering15分钟
1 个练习
Module 1 Graded Quiz30分钟
2
完成时间为 7 小时

Module 2: Visual Features - Detection, Description and Matching

6 个视频 (总计 44 分钟), 5 个阅读材料, 1 个测验
6 个视频
Lesson 2: Feature Descriptors6分钟
Lesson 3 Part 1: Feature Matching7分钟
Lesson 3 Part 2: Feature Matching: Handling Ambiguity in Matching5分钟
Lesson 4: Outlier Rejection8分钟
Lesson 5: Visual Odometry9分钟
5 个阅读材料
Supplementary Reading: Feature Detectors and Descriptors30分钟
Supplementary Reading: Feature Matching15分钟
Supplementary Reading: Feature Matching15分钟
Supplementary Reading: Outlier Rejection15分钟
Supplementary Reading: Visual Odometry10分钟
3
完成时间为 3 小时

Module 3: Feedforward Neural Networks

6 个视频 (总计 58 分钟), 6 个阅读材料, 1 个测验
6 个视频
Lesson 2: Output Layers and Loss Functions10分钟
Lesson 3: Neural Network Training with Gradient Descent10分钟
Lesson 4: Data Splits and Neural Network Performance Evaluation8分钟
Lesson 5: Neural Network Regularization9分钟
Lesson 6: Convolutional Neural Networks9分钟
6 个阅读材料
Supplementary Reading: Feed-Forward Neural Networks15分钟
Supplementary Reading: Output Layers and Loss Functions15分钟
Supplementary Reading: Neural Network Training with Gradient Descent15分钟
Supplementary Reading: Data Splits and Neural Network Performance Evaluation10分钟
Supplementary Reading: Neural Network Regularization15分钟
Supplementary Reading: Convolutional Neural Networks10分钟
1 个练习
Feed-Forward Neural Networks30分钟
4
完成时间为 3 小时

Module 4: 2D Object Detection

4 个视频 (总计 52 分钟), 4 个阅读材料, 1 个测验
4 个视频
Lesson 2: 2D Object detection with Convolutional Neural Networks11分钟
Lesson 3: Training vs. Inference11分钟
Lesson 4: Using 2D Object Detectors for Self-Driving Cars14分钟
4 个阅读材料
Supplementary Reading: The Object Detection Problem15分钟
Supplementary Reading: 2D Object detection with Convolutional Neural Networks30分钟
Supplementary Reading: Training vs. Inference45分钟
Supplementary Reading: Using 2D Object Detectors for Self-Driving Cars30分钟
1 个练习
Object Detection For Self-Driving Cars30分钟
4.6
15 条评论Chevron Right

来自Visual Perception for Self-Driving Cars的热门评论

创建者 RGOct 7th 2019

Many thanks for this amazing course!!!! was very hard to me but I have learned a lot!!! Thanks!!!

创建者 AAJul 18th 2019

Content is great but lack of instructor support makes the course hard to understand.

讲师

Avatar

Steven Waslander

Associate Professor
Aerospace Studies

关于 多伦多大学

Established in 1827, the University of Toronto is one of the world’s leading universities, renowned for its excellence in teaching, research, innovation and entrepreneurship, as well as its impact on economic prosperity and social well-being around the globe. ...

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