Category: Other

CamCal 004 What does R look like?

Highlights: In this post we will continue working on camera calibration, and we will take a detailed look how does \(R \) look like. If you don’t remember what is \(R \), that is a rotation operator. Tutorial Overview: Intro Example: Rotation About Z-Axis Rotation in Homogeneous Coordinates Rigid Transformation 1. Intro There are two ways to think about this rotation operator. First, we will think in a hard way. \(_{A}^{B}\textrm{R} \) expresses how each…
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#FA 002 Face Detection with OpenCV in Images

Face detection represents the ability of a computer technology to locate peoples’s faces within digital images. Face detection applications employ algorithms focused on detecting human faces within larger images that also contain other objects such as landscapes, houses, cars and others. Table of Contents: Import required packages Select the network Preprocess the image, standardise, mean subtraction Process the image with a Neural Network Analyze detections The importance of face detection can be seen as: The…
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FR 001 Face Recognition with Celebrities

Highlights: In the world today, there are a lot of visual data and it is important how we utilize and interpret this data. The project is more of an evolution between traditional algorithms and deep learning techniques. How accurately can we predict and find the correct name of the celebrity in a given image or video frame. Tutorial Overview: This post covers the following topics: What is a facial recognition system? Applications of face recognition.…
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#008 TF 2.0 An implementation of a Shallow Neural Network in tf.keras – digits dataset

In this post we will see how we can classify handwritten digits using shallow neural network implemented with tf.keras. Table of Contents: Load the digit dataset Implementing a Neural Network Visualization and Testing 1. Load the digits dataset First, let us import all necessary libraries. After imports, we can use imported module to load digits data. The load_digits() function will just download data and we need to split it into train and test sets. We can also…
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#K An implementation of a Shallow Neural Network in Keras – Spirals dataset

In this post we will see how we can classify a spirals dataset with a shallow neural network implemented in Keras. Let’s start by importing libraries that we will need in the our code. Here, we will make our dataset and divide it into training and testing set. Let’s now create a shallow neural network! Next, we will make predictions and plot the accuracy and loss function of our model. Now, we will make some…
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