Tutorials
Here is a listing of all the tutorials on this AI Shack
Tracks
Tracks are a series of tutorials put together in a logical order
Image processing algorithms (level 1)
Figure out how some of the basic algorithms in computer vision work. This track takes you through a handful of everyday use algorithms.
Image processing algorithms (level 2)
Learn how commonly used algorithms in computer vision work under the hood. You'll learn a wide variety of techniques to add to your arsenal.
Categories
Some broad categories of topics covered on AI Shack. Pick one to drill down.
All tutorials
- Generating Multivariate Gaussian Random Numbers
- Expectation Maximization with Gaussian Mixture Models 1 2
- K-Nearest Neighbours: Classify (recognize) things
- Obstacle avoidance with the Bug-1 algorithm
- K-Means clustering
- Linear separability
- Solving for intersection of lines efficiently
- Converting lines from normal to slope-intercept form
- Finding dominant colors in an image 1 2 3
- The Canny Edge Detector 1 2
- Image Moments
- A super fast thresholding technique
- The Sobel and Laplacian Edge Detectors
- Fast connected components labeling
- Convolutions 1 2
- Calibrating & Undistorting with OpenCV in C++ (Oh yeah)
- Calibrating a camera: Theory
- Two major physical defects in cameras
- Mathematical Morphology 1 2
- Histograms: From simplest to the most complex
- SIFT: Theory and Practice 1 2 3 4 5 6 7
- Corner Detection in OpenCV
- Fundamentals of Features and Corners 1 2 3 4 5
- Connected Component Labelling 1 2 3
- Circle Hough Transform
- The Hough Transform 1 2
- Template matching
- Normalized RGB
- Noise reduction by averaging 1 2
- Noise Models 1 2
- Color spaces 1 2
- Thresholding
- An introduction to contours
- Scanning QR Codes 1 2 3 4
- SuDoKu Grabber in OpenCV 1 2 3 4 5
- Tracking colored objects in OpenCV
- The OpenCV 2 Computer Vision Application Programming Cookbook
- Community Core Vision: An app for simple vision stuff
- Learning OpenCV: Computer Vision using the OpenCV Library
- K-Nearest Neighbors in OpenCV
- Image Convolutions in OpenCV
- K-Means clustering in OpenCV
- OpenCV's C++ interface
- Integral images in OpenCV
- Mathematical Morphology in OpenCV
- Using OpenCV on Windows
- OpenCV vs VXL vs LTI: Performance Test
- Transparent image overlays in OpenCV
- Drawing Histograms in OpenCV
- Accessing Histogram Data
- Histograms with functions of OpenCV
- Implementing SIFT in OpenCV
- Subpixel corners in OpenCV
- Efficiently accessing matrices
- Memory layout of matrices of multi-dimensional objects
- Hough circles in OpenCV
- Hough transform in OpenCV
- Cropping robotics arena boundaries: Implementation
- Cropping robotics arena boundaries
- 2D matrices with CvMat in OpenCV
- Primitive structures in OpenCV
- Installing and configuring OpenCV 2.0 on Windows
- Capturing images with DirectX
- HighGUI: Creating Interfaces
- Capturing images
- Filtering images
- Hello World! with Images
- Installing and Getting OpenCV running
- Why OpenCV?
- OpenCV Memory Management
- Generating uniform noise
- Simple motor driver circuit
- How servo motors work?
- 78xx voltage regulator
- L293D: An H-Bridge
- Pulse Width Modulators
- Robocup soccer rules for the Small Sized League (SSL)
- The three motors you'll ever use in robotics
- Identification tags in competitions
- 7 unique neural network architectures
- Dictomizer examples: AND/OR gates
- A single neuron Dictomizer
- The modern artificial neuron
- First artificial neurons: The McCulloch-Pitts model
- All about biological neurons
- What exactly is a Neural Network?
Machine Learning
SVMs, neural networks, k-means and any related machine learning techniques that can help augment your AI journey!
Computer Vision
Core concepts in image processing and computer vision are covered here. Things like convolutions, hough transforms, camera calibration are here! Most of these are programming agnostic - however, I've mostly used OpenCV to implement these ideas.
Projects
Long form articles that take an idea and build them from starting to the end. These are very insightful and help understand the mathematical mumbo-jumbo with a real-life use-case!
Reviews
My take on things I've used personally and I endorse. Articles here include books, software, etc.
OpenCV
Ideas or concepts focusing primarily on OpenCV go here. It might be something idiosyncratic to OpenCV (like cv::Mat) or a useful tip. Things like that go here!
Electronics
Occasionally I write about electronics, microcontrollers and Raspberry Pis. These tutorials are somehow related to AI - but focus more on the electronics aspect.
Robotics
These articles are a bit more focused on robotics. Things like competitive robotics, industrial robotics, etc go here. Self-driven cars belong here as well!
Neural Networks
Neural networks have gotten extremely useful lately and this section describes how to use them in your own attempts at understanding the world.
