Learn to implement popular CV algorithms with OpenCV python library
Note: Course Free for limited time and limited users(500 limit) so Enroll ASAP. If not free it means you are late. Scroll Down and click Enroll Now button to get enrolled
What You will Learn
- Learn fundamentals of Computer Vision
- Understand state of art image and video processing Algorithms in CV
- Understand application of Deep Learning Models in the CV
- Learn to implement CV algorithms with OpenCV python library
Scroll Down and click Enroll Now Button to get enrolled into the Free Course
Description
Learn fundamentals of Computer Vision with state of art image and video processing Algorithms.
Course Structure
Introduction:
Introduction
Real world Applications
Popular Computer Vision Techniques:
Image Segmentation
Demo – Image Segmentation
Edge Detection
Demo – Edge Detection
Feature Extraction
Demo – Feature Extraction
Application of CV techniques
Object Detection, Tracking and Classification:
Object Detection
Object Tracking
Image Classification
Demo: Image Classification
Challenges in CV
Deep Learning for Computer Vision:
What is Deep Learning?
Convolutional Neural Network (CNN)
Demo – CNN
Transfer Learning
Benefits of Deep Learning in CV
Image Recognition:
Face Detection and Recognition
Demo – Face Detection
Optical Character Recognition (OCR)
Demo – OCR
Advanced Techniques – Panorama Creation:
Image Registration
Image Stitching
Demo – Image Stitching
Motion Analysis:
Motion Analysis
Video Processing
Background Subtraction
Demo: Background Subtraction
Realtime Video Processing:
Realtime Video Processing
Demo – Object Detection
Application in Robotics
Requirements
Basics knowledge of computer programming
Familiar with python programming language and any python IDE (like PyCharm)
Windows / Linux / Mac OS X Machine with Internet
Content team
Expert: Arunkumar Krishnan
Production: Vishnu Sakthivel, Visshwa Balasubramanian
What you will learn?
Learn fundamentals of Computer Vision
Understand state of art image and video processing Algorithms in CV
Understand application of Deep Learning Models in the CV
Learn to implement CV algorithms with OpenCV python library
Who this course is for:
Freshers and experienced professionals interested in learning ‘Computer Vision’
Ye
Requirements
Familiar with python programming language and any python IDE (like PyCharm)
Course Content
- 8 sections • 42 lectures • 48m total length
- Introduction
- Real word Applications
- Summary
- Image Segmentation
- Demo – Image Segmentation
- Edge Detection
- Demo – Edge Detection
- Feature Extraction
- Demo – Feature Extraction
- Application of CV techniques
- Summary
- Popular CV techniques
- Object Detection
- Object Tracking
- Image Classification
- Demo: Image Classification
- Challenges in CV
- Summary
- Object Detection, Tracking and Classification
- What is Deep Learning?
- Convolutional Neural Network (CNN)
- Demo – CNN
- Transfer Learning
- Demo – Transfer Learning
- Benefits of Deep Learning in CV
- Summary
- Deep Learning in Computer Vision
- Face Detection and Recognition
- Demo – Face Detection
- Optical Character Recognition (OCR)
- Demo – OCR
- Summary
- Image Recognition
- Image Registration
- Image Stitching
- Demo – Image Stitching
- Summary
- Advanced Techniques – Panorama Creation
- Motion Analysis
- Video Processing
- Background Subtraction
- Demo: Background Subtraction
- Summary
- Motion Analysis
- Realtime Video Processing
- Demo – Object Detection
- Application in Robotics
- Summary
- Realtime Video Processing
Note: Course Free for limited time and limited users(500 limit) so Enroll ASAP. If not free it means you are late.
