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This course is about the fundamental concept of image recognition, focusing on face detection. These topic is getting very hot nowadays because these learning algorithms can be used in several fields from software engineering to crime investigation.
We will talk about the theoretical background for face recognition algorithm then we are going to implement these problems together.
The first chapter is about static face detection: at the end of the chapter we will be able to construct applications capable of detecting faces on static images or pictures. In the second chapter we will consider a real-time problem: how to be able to detect faces in real-time, for example on webcamera videos.
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Desktop, iOS and Android.
Certificate of completion.
|Section 1: Introduction|
Face detection theoryPreview
|Section 2: Face Detection Application|
Setting up the GUI
GUI - loading images
Showing detected faces
Cascade classifier parameters
Tuning the parameters
|Section 3: Webcam Application|
Webcam application overview
Webcam application GUI
Webcam face detection
|Section 4: Source Code|
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My name is Balazs Holczer. I am from Budapest, Hungary. I am qualified as a physicist and later on I decided to get a master degree in applied mathematics. At the moment I am working as a simulation engineer at a multinational company. I have been interested in algorithms and data structures and its implementations especially in Java since university. Later on I got acquainted with machine learning techniques, artificial intelligence, numerical methods and recipes such as solving differential equations, linear algebra, interpolation and extrapolation. These things may prove to be very very important in several fields: software engineering, research and development or investment banking. I have a special addiction to quantitative models such as the Black-Scholes model, or the Merton-model. Quantitative analysts use these algorithms and numerical techniques on daily basis so in my opinion these topics are definitely worth learning.