Download Course Outline for Computer Vision and more Summaries Computer Vision in PDF only on Docsity!
WEEK 1: INTRODUCTION OF COMPUTER VISION
Lesson I: What is Computer Vision? A. Distinguishing computer vision from related fields
- Image processing
- Machine vision
- Computer vision
WEEK 2: INDUSTRY APPLICATIONS
Lesson II: Industry applications A. Retail
- Behavioral tracking
- Inventory management B. Manufacturing C. Healthcare D. Autonomous vehicles E. Insurance F. Agriculture G. Defense and Security
WEEK 3: TYPICAL TASKS IN COMPUTER VISION
Lesson III: Typical tasks in computer vision A. Image classification B. Localization C. Object detection D. Object identification E. Instance segmentation F. Object tracking
WEEK 4: HOW IT WORKS
Lesson IV: How it works
A. A general strategy
- Four steps outline a general approach to building a computer vision model using CNNs B. Existing datasets C. Training an object detection model
- Viola and Jones approach
- CNN-based approaches
WEEK 5: Preliminary Exam
WEEK 6-7: BUSINESS USE CASES
Lesson VI: Business use cases A. Visual Search Engines B. Face recognition at Facebook C. Amazon Go D. Tesla Autopilot E. Microsoft’s InnerEye
WEEK 8: I’M NOT GOOGLE, WHAT NOW?
Lesson VII: I’m not google, What now?
WEEK 9: HOW TO REALIZE A COMPUTER VISION PROJECT
Lesson VllI: How to realize a computer vision project A. Should the computer vision solution reduce costs or increase revenue? B. How are you going to measure the success of your computer vision project? C. Is the access to information guaranteed? D. Is your organization collecting the right data? E. Is your organization collecting the data in the right format?
