Acerca de este Curso

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Certificado para compartir
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100 % en línea
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Fechas límite flexibles
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Nivel avanzado

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

Aprox. 31 horas para completar
Inglés (English)

Qué aprenderás

  • 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

Certificado para compartir
Obtén un certificado al finalizar
100 % en línea
Comienza de inmediato y aprende a tu propio ritmo.
Fechas límite flexibles
Restablece las fechas límite en función de tus horarios.
Nivel avanzado

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

Aprox. 31 horas para completar
Inglés (English)

Instructor

ofrecido por

Placeholder

Universidad de Toronto

Programa - Qué aprenderás en este curso

Semana
1

Semana 1

2 horas para completar

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

2 horas para completar
4 videos (Total 18 minutos), 4 lecturas
4 videos
Welcome to the course4m
Meet the Instructor, Steven Waslander5m
Meet the Instructor, Jonathan Kelly2m
4 lecturas
Course Prerequisites15m
How to Use Discussion Forums15m
How to Use Supplementary Readings in This Course15m
Recommended Textbooks15m
7 horas para completar

Module 1: Basics of 3D Computer Vision

7 horas para completar
6 videos (Total 43 minutos), 4 lecturas, 2 cuestionarios
6 videos
Lesson 1 Part 2: Camera Projective Geometry8m
Lesson 2: Camera Calibration7m
Lesson 3 Part 1: Visual Depth Perception - Stereopsis7m
Lesson 3 Part 2: Visual Depth Perception - Computing the Disparity5m
Lesson 4: Image Filtering7m
4 lecturas
Supplementary Reading: The Camera Sensor30m
Supplementary Reading: Camera Calibration15m
Supplementary Reading: Visual Depth Perception30m
Supplementary Reading: Image Filtering15m
1 ejercicio de práctica
Module 1 Graded Quiz30m
Semana
2

Semana 2

7 horas para completar

Module 2: Visual Features - Detection, Description and Matching

7 horas para completar
6 videos (Total 44 minutos), 5 lecturas, 1 cuestionario
6 videos
Lesson 2: Feature Descriptors6m
Lesson 3 Part 1: Feature Matching7m
Lesson 3 Part 2: Feature Matching: Handling Ambiguity in Matching5m
Lesson 4: Outlier Rejection8m
Lesson 5: Visual Odometry9m
5 lecturas
Supplementary Reading: Feature Detectors and Descriptors30m
Supplementary Reading: Feature Matching15m
Supplementary Reading: Feature Matching15m
Supplementary Reading: Outlier Rejection15m
Supplementary Reading: Visual Odometry10m
Semana
3

Semana 3

3 horas para completar

Module 3: Feedforward Neural Networks

3 horas para completar
6 videos (Total 58 minutos), 6 lecturas, 1 cuestionario
6 videos
Lesson 2: Output Layers and Loss Functions10m
Lesson 3: Neural Network Training with Gradient Descent10m
Lesson 4: Data Splits and Neural Network Performance Evaluation8m
Lesson 5: Neural Network Regularization9m
Lesson 6: Convolutional Neural Networks9m
6 lecturas
Supplementary Reading: Feed-Forward Neural Networks15m
Supplementary Reading: Output Layers and Loss Functions15m
Supplementary Reading: Neural Network Training with Gradient Descent15m
Supplementary Reading: Data Splits and Neural Network Performance Evaluation10m
Supplementary Reading: Neural Network Regularization15m
Supplementary Reading: Convolutional Neural Networks10m
1 ejercicio de práctica
Feed-Forward Neural Networks30m
Semana
4

Semana 4

3 horas para completar

Module 4: 2D Object Detection

3 horas para completar
4 videos (Total 52 minutos), 4 lecturas, 1 cuestionario
4 videos
Lesson 2: 2D Object detection with Convolutional Neural Networks11m
Lesson 3: Training vs. Inference11m
Lesson 4: Using 2D Object Detectors for Self-Driving Cars14m
4 lecturas
Supplementary Reading: The Object Detection Problem15m
Supplementary Reading: 2D Object detection with Convolutional Neural Networks30m
Supplementary Reading: Training vs. Inference45m
Supplementary Reading: Using 2D Object Detectors for Self-Driving Cars30m
1 ejercicio de práctica
Object Detection For Self-Driving Cars30m

Reseñas

Principales reseñas sobre VISUAL PERCEPTION FOR SELF-DRIVING CARS

Ver todas las reseñas

Acerca de Programa especializado: Automóviles de auto conducción

Automóviles de auto conducción

Preguntas Frecuentes

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