Key objectives of the course include following key topics:
Explain Vision AI experience using 2 Vision AI case studies
Finally, you will be able to Understand components of a Vision AI solution
This course is divided into multiple sections.
Section 1 provides an introduction to the course including course outline, audience, expected outcome, and authors for the course.
In section 2, we will describe what is a Vision AI and how it is being used in classifying and cataloging various image and videos. We will cover key concepts behind Vision VI and its 5 complexity levels'
In section 3, we will take a series of use cases in four different categories like
Document Understanding
Scene Analysis
Entity Recognition
Image generation
and will show you different use cases associated with above categories where different vision concepts are employed.
In Section 4, we will introduce you to key technologies behind Vision AI like
Deep Learning
Computer Vision models like CNN, RNN and Faster R-CNN
Transfer Learning and popular library VGG-16
Embedding
Computer Vision open-source library Keras
In Section 5, we will cover first good example of Vision AI for analyzing Payment protection Plan to interpret payroll forms. US Government released more than 1 trillion dollars to support small businesses economically impacted by COVID. As small business applications grew, there was need for automated extraction of payroll information from applicant forms, many of which were filled by hand. We will describe problem, solution components and benefit case for this problem.
In section 6, we will introduce second case study on Image Classification and Item Identification for Retail/warehouse outlets, We will describe problem, user persona, solution components and benefit case for this problem.
In the last section, we will summarize the course contents and will introduce several commercial offerings in this area. We will also discuss related references and courses to move forward with your Vision AI learning.
