MathWorks - Deep Learning for Object Detection
- Offered byCoursera
Deep Learning for Object Detection at Coursera Overview
Duration | 8 hours |
Start from | Start Now |
Total fee | Free |
Mode of learning | Online |
Official Website | Explore Free Course  |
Credential | Certificate |
Deep Learning for Object Detection at Coursera Highlights
- Earn a certificate after completion of the course
- Assignment and projects for practice
- Financial aid available
Deep Learning for Object Detection at Coursera Course details
- Retrain popular YOLO deep learning models for your applications
- Visualize results to gain insights into model performance
- Evaluate detection models by examining both class and location accuracy.
- Analyze labeled images to identify and fix potential data shortcomings
- Detecting and locating objects is one of the most common uses of deep learning for computer vision
- Applications include helping autonomous systems navigate complex environments, locating medical conditions like tumors, and identifying ready-to-harvest crops in agriculture
- In the course projects, you will apply detection models to real-world scenarios and train a model to detect various parking signs. Completing this course will give you the skills to train detection models for your application.
- By the end of this course, you will be able to:
- Explain how deep learning networks locate and classify objects in images
- Retrain popular YOLO deep learning models for your application
- Use a variety of metrics to evaluate prediction results
- Visualize results to gain insights into model performance
- Improve model performance by adjusting important model parameters
- Analyze labeled images to identify and fix potential shortcomings in your data
- For the duration of the course, you will have free access to MATLAB, software used by top employers worldwide
- The courses draw on the applications using MATLAB, so you spend less time coding and more time applying deep learning concepts.
Deep Learning for Object Detection at Coursera Curriculum
Detecting Objects with Pre-trained Models
Deep Learning for Computer Vision
Deep Learning for Object Detection
Introduction to Object Detection with CNNs
Using Pre-trained Object Detectors
Meet Your Instructors
Course files and MATLAB
Installing Pre-trained Object Detectors
Using Detection Models on Images and Videos
YOLO Detectors in MATLAB Reference
Getting Started with Object Detection
Training Object Detection Models
Overview of Training Object Detection Models
Labeling your Images
Analyzing Your Labeled Data
Peforming Transfer Learning with Object Detection Models
Introduction to the Datasets
Considerations When Labeling Images
Analyzing Your Data
Transfer Learning for Fasteners Detection
Week 2 Quiz
Evaluating Object Detection Models
Evaluating Object Detection Models
Addressing Common Issues in Detection
Evaluating Models in MATLAB
Addressing Common Issues
Additional Tips for Improving Models
Assessment Instructions
Concept Check
Evaluating Detection Models
Final Project: Train and Evaluate a Detection Model
Introduction to the Final Project
Summary of Deep Learning for Object Detection
Overview of the Data
Your Tasks for Part 1
Your Tasks for Part 2
Our trained model
Your Tasks for Part 3
What's Next?
Analyze the Labeled Training Images
Training a Model
Evaluate Your Model
Deep Learning for Object Detection at Coursera Admission Process
Important Dates
Other courses offered by Coursera
Student Forum
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