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Deep Learning for Object Detection

Detecting and locating objects is one of the most common uses of deep learning for computer vision. Applications include helping autonomous systems navigate...

By Mehdi Alemi on Coursera

About This Course

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.

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Frequently Asked Questions

How much does Deep Learning for Object Detection cost?

Visit the Deep Learning for Object Detection course page for current pricing and available discounts.

Who teaches Deep Learning for Object Detection?

Deep Learning for Object Detection is taught by Mehdi Alemi, MathWorks.

What skill level is Deep Learning for Object Detection for?

This course is designed for all levels learners.

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Students0
DurationSelf-paced
LevelAll Levels
Languageen
PlatformCoursera
InstructorMehdi Alemi