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Visual Perception for Self-Driving Cars
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Visual Perception for Self-Driving Cars

Master computer vision techniques for autonomous vehicles: camera calibration, object detection, and semantic segmentation.

Course Cost

Free course

Advanced

Skill Level

28 Hours

Self-paced lessons

This course cannot be purchased separately - to access the complete learning experience, graded assignments, and earn certificates, you'll need to enroll in the full Self-Driving Cars Specialization program. You can audit this specific course for free to explore the content, which includes access to course materials and lectures. This allows you to learn at your own pace without any financial commitment.

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4.7

42,269 Enrolled

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English

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olive-leaves-logo

4.7

42,269 Enrolled

olive-leaves-logo

English

What you'll learn

  • Master pinhole camera models and camera calibration techniques

  • Implement feature detection and matching algorithms

  • Develop custom convolutional neural networks

  • Create object detection and tracking systems

  • Apply semantic segmentation for surface estimation

  • Build complete perception systems for autonomous vehicles

Skills you'll gain

Computer Vision
Deep Learning
Object Detection
Semantic Segmentation
Camera Calibration
Neural Networks
Feature Detection
Visual Odometry
Image Processing
CARLA Simulator

This course includes:

4.45 Hours PreRecorded video

4 quizzes

Access on Mobile, Tablet, Desktop

FullTime access

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Share your certificate with prospective employers and your professional network on LinkedIn.

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Top companies offer this course to their employees

Top companies provide this course to enhance their employees' skills, ensuring they excel in handling complex projects and drive organizational success.

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There are 7 modules in this course

This comprehensive course covers fundamental computer vision techniques essential for autonomous vehicle perception systems. Students learn advanced concepts including camera models and calibration, feature detection and matching, convolutional neural networks, object detection, and semantic segmentation. The curriculum combines theoretical foundations with practical applications using the CARLA simulator. Through hands-on programming assignments, participants develop skills in implementing real-world perception systems for self-driving cars.

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

Module 1 · 1 Hours to complete

Module 1: Basics of 3D Computer Vision

Module 2 · 7 Hours to complete

Module 2: Visual Features - Detection, Description and Matching

Module 3 · 7 Hours to complete

Module 3: Feedforward Neural Networks

Module 4 · 2 Hours to complete

Module 4: 2D Object Detection

Module 5 · 3 Hours to complete

Module 5: Semantic Segmentation

Module 6 · 2 Hours to complete

Module 6: Putting it together - Perception of dynamic objects in the drivable region

Module 7 · 6 Hours to complete

Fee Structure

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Faculties

These are the expert instructors who will be teaching you throughout the course. With a wealth of knowledge and real-world experience, they're here to guide, inspire, and support you every step of the way. Get to know the people who will help you reach your learning goals and make the most of your journey.

Visual Perception for Self-Driving Cars

Advanced

Skill Level

28 Hours

Self-paced lessons

Course Cost

Free course

Completion

CERTIFICATE

Frequently asked Questions

Below are some of the most commonly asked questions about this course. We aim to provide clear and concise answers to help you better understand the course content, structure, and any other relevant information. If you have any additional questions or if your question is not listed here, please don't hesitate to reach out to our support team for further assistance.