Computer Vision Essentials

Course Content

Computer Vision Essentials

Computer Vision Essentials

1. Introduction to Computer Vision

What is Computer Vision?Fundamentals of Image Processing Linear Algebra for Image Manipulation

2. Image Processing with OpenCV

Basic Transformations Fourier Transform Low-pass and High-pass Filters Noise Reduction and Smoothing Histogram Equalization Super-Resolution Techniques Edge Detection Corner and Blob Detection

3. Convolutional Neural Networks

Introduction to Convolutional Neural Networks Convolution Layers Pooling Layers Flattening Activation Functions Overview of Popular CNN Models Challenge: Building a CNN

4. Object Detection

Object Localization Object Detection Bounding Box Predictions Intersection Over Union (IoU) and Evaluation Metrics Non-Max Suppression (NMS)Anchor Boxes YOLO Model Overview Challenge: Object Detection with Custom Model and YOLO

5. Advanced Topics Overview

Transfer Learning in Computer Vision Overview of Face Recognition Overview of Image Generation

What is Computer Vision?

Real-world applications of computer vision include:

Computer vision encompasses a variety of tasks that enable machines to understand and process visual data effectively:

Image classification;
Object detection;
Image segmentation;
Face & person recognition;
Edge detection;
Image restoration;
Matching scene reconstruction;
Video motion analysis.

Everything was clear?

Thanks for your feedback!

Section 1. Chapter 1

Ask AI

Ask AI

Ask anything or try one of the suggested questions to begin our chat

Course Content

Computer Vision Essentials

Computer Vision Essentials

1. Introduction to Computer Vision

What is Computer Vision?Fundamentals of Image Processing Linear Algebra for Image Manipulation

2. Image Processing with OpenCV

Basic Transformations Fourier Transform Low-pass and High-pass Filters Noise Reduction and Smoothing Histogram Equalization Super-Resolution Techniques Edge Detection Corner and Blob Detection

3. Convolutional Neural Networks

Introduction to Convolutional Neural Networks Convolution Layers Pooling Layers Flattening Activation Functions Overview of Popular CNN Models Challenge: Building a CNN

4. Object Detection

Object Localization Object Detection Bounding Box Predictions Intersection Over Union (IoU) and Evaluation Metrics Non-Max Suppression (NMS)Anchor Boxes YOLO Model Overview Challenge: Object Detection with Custom Model and YOLO

5. Advanced Topics Overview

Transfer Learning in Computer Vision Overview of Face Recognition Overview of Image Generation

What is Computer Vision?

Real-world applications of computer vision include:

Computer vision encompasses a variety of tasks that enable machines to understand and process visual data effectively:

Image classification;
Object detection;
Image segmentation;
Face & person recognition;
Edge detection;
Image restoration;
Matching scene reconstruction;
Video motion analysis.

Everything was clear?

Thanks for your feedback!

Section 1. Chapter 1

some-alt