Course Outline for Computer Vision, Summaries of Computer Vision

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 1. Image processing 2. Machine vision 3. Computer vision WEEK 2: INDUSTRY APPLICATIONS Lesson II: Industry applications A. Retail 1. Behavioral tracking 2. 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 1. Four steps outline a general approach to building a computer vision model using CNNs B. Existing datasets C. Training an object detection model 1. Viola and Jones approach 2. 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?