Artificial Intelligence

Computer Vision Essentials

4.47 (220 Ratings)
Advanced

Advanced

Skill level
offer

Free

Course cost

About this course

Computer vision (CV) is a set of techniques that are used to help machines to “see” and comprehend what is contained in digital imagery such as photos and videos. It has varied applications such as in medical imaging, motion capture, surveillance, automating retail checkouts, and in optical character recognition. This course starts with the basic steps of digitizing images, sampling them and compressing them (quantization). It then covers various methods to work with images including classification, identification, detection, etc.

Skills covered

  • check Working with Images
  • check Convolution
  • check Pooling
  • check Transfer learning
  • check Convolutional Neural Networks

Course Syllabus

Computer Vision Essentials

  • play Working with Images_Introduction
  • play Working with Images - Digitization, Sampling, and Quantization
  • play Working with images - Filtering
  • play Introduction to Convolutions
  • play 2D convolutions for Images
  • play Convolution - Forward
  • play Convolution - Backward
  • play Transposed Convolution and Fully Connected Layer as a Convolution
  • play Pooling : Max Pooling and Other pooling options
  • play CNN Architectures and LeNet Case Study
  • play GPU vs CPU
  • play Transfer Learning Principles and Practice
  • play Visualization (run pacakge, occlusion experiment)

Course Certificate

Get Computer Vision Essentials course completion certificate from Great learning which you can share in the Certifications section of your LinkedIn profile, on printed resumes, CVs, or other documents.

GL Academy Sample Certificate

Discussion on Computer Vision Essentials

8 Comments

A

Am interested in this topic computer version, kindly shed more light on the same

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Computer vision related to AI starts with convolution neural network.
Opencv, pillow libraries are used for processing image type data.They dont perform AI based models on image data.

For detailed information you can take up the free course from GL academy:-

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Where can we learn all the basics for computer vision related to AI?Is OpenCV the only thing or are there any alternatives?If yes then how to go about it & if no then how to go about other options ? Any resources?

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