Description

Computer Vision is a subarea of Artificial Intelligence focused on creating systems that can process, analyze and identify visual data in a similar way to the human eye. There are many commercial applications in various departments, such as: security, marketing, decision making and production. Smartphones use Computer Vision to unlock devices using face recognition, self-driving cars use it to detect pedestrians and keep a safe distance from other cars, as well as security cameras use it to identify whether there are people in the environment for the alarm to be triggered.

In this course you will learn everything you need to know in order to get in this world. You will learn the step-by-step implementation of the 14 (fourteen) main computer vision techniques. If you have never heard about computer vision, at the end of this course you will have a practical overview of all areas. Below you can see some of the content you will implement:

   Detect faces in images and videos using OpenCV and Dlib libraries
   Learn how to train the LBPH algorithm to recognize faces, also using OpenCV and Dlib libraries
   Track objects in videos using KCF and CSRT algorithms
   Learn the whole theory behind artificial neural networks and implement them to classify images
   Implement convolutional neural networks to classify images
   Use transfer learning and fine tuning to improve the results of convolutional neural networks
   Detect emotions in images and videos using neural networks
   Compress images using autoencoders and TensorFlow
   Detect objects using YOLO, one of the most powerful techniques for this task
   Recognize gestures and actions in videos using OpenCV
   Create hallucinogenic images using the Deep Dream technique
   Combine style of images using style transfer
   Create images that don’t exist in the real world with GANs (Generative Adversarial Networks)
   Extract useful information from images using image segmentation

You are going to learn the basic intuition about the algorithms and implement some project step by step using Python language and Google Colab
Who this course is for:

   Beginners who are starting to learn Computer Vision
   Undergraduate students who are studying subjects related to Artificial Intelligence
   People who want to solve their own problems using Computer Vision
   Students who want to work in companies developing Computer Vision projects
   People who want to know all areas inside Computer Vision, as well as know the problems that these techniques are able to solve
   Anyone interested in Artificial Intelligence or Computer Vision
   Data scientists who want to grow their portfolio
   Professionals who want to understand how to apply Computer Vision to real projects

Requirements

   Programming logic
   Basic Python programming

Last Updated 3/2021