Computer Vision Course

Computer Vision free course serves as an introduction to computer vision, covering the basics of image generation, camera imaging geometry, feature detection and matching, and multiview geometry, including stereo, motion estimation and tracking, and classification. For applications such as detecting known models in images, depth recovery from the stereo, camera calibration, image stabilisation, automatic alignment (for example, panoramas), tracking, and action identification, we’ll create the fundamental techniques.

What will you learn Computer Vision Free Course?

1. Computer Vision Applications
2. Introduction to CNN (Convolutional Neural Network)
3. Neural Networks
4. Forward Propagation
5. Backward Propagation
6. Kernel
7. Strides
8. Padding
9. Pooling Layer
10. Fully Connected Layer
11. What is Open CV
12. Image Processing
13. Video Processing
14. Video Analysis
15. Feature Detection

Requirement

This course is based on Python, so it requires an understanding of that.

Description

A warm welcome to the Computer Vision course.

Computer vision is an advanced Artificial intelligence field. This enables the computer to gain high-level understanding from digital images or videos.
There are many excellent applications of computer vision. For example, in COVID-19 time, the number of customers inside a store can be counted, or the social distancing between customers can be measured; Computer vision is even used for detecting covid-19 cases from the chest X-ray. Apart from that, the Facebook photo auto-tagging feature and image gender transformation used by FaceApp are other example s of usage of computer vision technology.

This computer vision Training will take you through various concepts such as – Convolutional Neural Network (CNN), Neural Networks, Forward & Backward Propagation, CNN architecture – Kernel, Strides, Padding. We will be using the OpenCV library and will see its usage for Image Processing, Video Processing, Video Analysis, and Feature Detection.

So, let’s start, and we will see you in the course.

Who is this course for?

1. College Freshers
2. Anyone who is willing to learn Computer vision in simple and easy steps