Introduction to Computer Vision
Introduction to Computer Vision, available at $54.99, has an average rating of 4.5, with 52 lectures, based on 1 reviews, and has 18 subscribers.
You will learn about Become an advanced, confident, and modern Computer Vision expert from scratch How to think and work like a developer: problem-solving, researching, workflows Digital image processing: gray level transformations, geometric transformations, convolution, image enhancement and smoothing, morphological filters, etc. Get fast and friendly support in the Q&A area This course is ideal for individuals who are Take this course if you want to start your journey in Computer Vision or Take this course if you have been trying to learn Computer Vision but: 1) still don't really understand Computer Vision, or 2) still don't feel confident to work real projects It is particularly useful for Take this course if you want to start your journey in Computer Vision or Take this course if you have been trying to learn Computer Vision but: 1) still don't really understand Computer Vision, or 2) still don't feel confident to work real projects.
Enroll now: Introduction to Computer Vision
Summary
Title: Introduction to Computer Vision
Price: $54.99
Average Rating: 4.5
Number of Lectures: 52
Number of Published Lectures: 51
Number of Curriculum Items: 53
Number of Published Curriculum Objects: 52
Original Price: $29.99
Quality Status: approved
Status: Live
What You Will Learn
- Become an advanced, confident, and modern Computer Vision expert from scratch
- How to think and work like a developer: problem-solving, researching, workflows
- Digital image processing: gray level transformations, geometric transformations, convolution, image enhancement and smoothing, morphological filters, etc.
- Get fast and friendly support in the Q&A area
Who Should Attend
- Take this course if you want to start your journey in Computer Vision
- Take this course if you have been trying to learn Computer Vision but: 1) still don't really understand Computer Vision, or 2) still don't feel confident to work real projects
Target Audiences
- Take this course if you want to start your journey in Computer Vision
- Take this course if you have been trying to learn Computer Vision but: 1) still don't really understand Computer Vision, or 2) still don't feel confident to work real projects
Do you want to start your journey in Computer Vision?
Or is it that Computer Vision interests you?
If you need a quick brush-up, or learning Computer Vision for the first time, you’ve come to the right place!
Let’s get started learning one of the most interesting computer science topics out there right now. There’s no need to fret if you haven’t coded before. This courses starts from scratch.
Computer Vision is an interdisciplinary scientific field that deals with how computers can gain high-level understanding from digital images or videos. From the perspective of engineering and computer science, it seeks to understand and automate tasks that the human visual system can do. This course will be a quick way to introduce to the Computer Vision world. You’ll be a whiz in no time.
We’ll begin with the basics of Computer Vision, learning about the digital image, discretization, domains and getting to know the image quantification. We’ll soon move on to the basics of image information retrieval in Computer Vision.
Now, after completing this Introduction Course you can finish your training with The Complete Computer Vision Course available in my udemy profile with more than 12 hours duration.
I hope you’re excited to dive into the World of Computer Vision with this course. Well, what are you waiting for? Let’s get started!
Course Curriculum
Chapter 1: Course Overview
Lecture 1: Course Introduction
Lecture 2: Learning MATLAB
Chapter 2: The Digital Image
Lecture 1: Basic Concepts
Lecture 2: Discretization of the Image
Lecture 3: Working with Images
Lecture 4: Domain Evaluation
Lecture 5: How to Save an Image
Lecture 6: Mesh Function
Chapter 3: Image Quantification
Lecture 1: Introduction to Colour Quantification
Lecture 2: RGB and HSI Models
Chapter 4: Image Preprocessing
Lecture 1: Introduction to Image Preprocessing
Lecture 2: Image Information Retrieval
Lecture 3: Gray Level Histogram
Lecture 4: Histogram Equalization
Lecture 5: Affine Transformation
Lecture 6: Arithmetic Operations
Lecture 7: Quality Control Project – Statement
Lecture 8: Quality Control Project – Solution – Part 1
Lecture 9: Quality Control Project – Solution – Part 2
Lecture 10: Introduction to Convolution
Lecture 11: Working with Convolution
Lecture 12: Image Noise and Smoothing Filters
Lecture 13: Contour Detection
Chapter 5: Morphological Image Processing
Lecture 1: Introduction to Morphological Image Processing
Lecture 2: Dilations
Lecture 3: Erosions
Lecture 4: Morphological Gradients
Lecture 5: Distance Transform
Lecture 6: Conditional Dilation and Reconstruction
Lecture 7: Challenge 1 – Wrench Reconstruction
Lecture 8: Challenge 2 – Greek Symbols
Lecture 9: Challenge 3 – Closed Holes
Lecture 10: Opening and Closing
Lecture 11: Gear Detection
Lecture 12: Skeletons
Lecture 13: Morphology for Multilevel Images
Chapter 6: MATLAB Fundamentals – Commands
Lecture 1: Introduction to Commands
Lecture 2: Output in MATLAB
Chapter 7: MATLAB Fundamentals – Variables
Lecture 1: Introduction to Variables
Lecture 2: Storage and Data Loading
Lecture 3: Using Constants and built-in Functions
Chapter 8: MATLAB Fundamentals – Desktop and Editor
Lecture 1: MATLAB Environment Overview
Lecture 2: MATLAB Editor
Chapter 9: MATLAB Fundamentals – Arrays
Lecture 1: Introduction to Arrays
Lecture 2: Arrays and Spacing
Lecture 3: Array Creation Functions
Lecture 4: Indexing
Lecture 5: Extracting Multiple Elements
Chapter 10: MATLAB Fundamentals – Plots
Lecture 1: Plotting Arrays
Lecture 2: Plots Annotation
Chapter 11: MATLAB Fundamentals – Electricity Usage Project
Lecture 1: Electricity Usage
Instructors
-
Lucas Bazilio
Engineer and Mathematician
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- 4 stars: 1 votes
- 5 stars: 0 votes
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