Advanced Deep Learning Techniques for Computer Vision
Master advanced computer vision: anomaly detection, data augmentation, and model deployment with MATLAB.
Master advanced computer vision: anomaly detection, data augmentation, and model deployment with MATLAB.
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 Deep Learning for Computer Vision 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.
Instructors:
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What you'll learn
Train and optimize anomaly detection models
Generate synthetic training data using augmentation
Implement AI-assisted auto-labeling workflows
Deploy models and integrate with external platforms
Skills you'll gain
This course includes:
0.7 Hours PreRecorded video
7 assignments
Access on Mobile, Tablet, Desktop
FullTime access
Shareable certificate
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There are 4 modules in this course
This advanced course focuses on specialized techniques in computer vision using deep learning. Students learn to train anomaly detection models for visual inspection and medical imaging, generate synthetic training data through augmentation, and implement AI-assisted labeling for efficient image annotation. The curriculum covers model deployment, third-party integration with platforms like PyTorch, and practical applications in industrial and medical domains.
Anomaly Detection
Module 1 · 2 Hours to complete
Data Augmentation
Module 2 · 1 Hours to complete
Model-Assisted Labeling
Module 3 · 1 Hours to complete
Creating Your Own Models
Module 4 · 1 Hours to complete
Fee Structure
Instructors
Manager Online Courses
Brandon Armstrong is a Principal Online Content Developer at MathWorks. He earned a Ph.D. in physics from the University of California at Santa Barbara in 2010.
Online Course Developer at MathWorks
Amanda Wang is an Online Course Developer at MathWorks, specializing in creating educational content related to MATLAB and its applications in computer vision and deep learning. She holds dual Bachelor's degrees in Mathematics with Computer Science and Business Analytics from the Massachusetts Institute of Technology (MIT), which she completed in 2020. Currently, Amanda is pursuing a Master’s degree in Computer Science from the University of Illinois Urbana-Champaign.
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Frequently asked questions
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