Online or onsite, instructor-led live Face Recognition training courses demonstrate through interactive hands-on practice the fundamentals and advanced concepts of Face Recognition.
Face Recognition training is available as "online live training" or "onsite live training". Online live training (aka "remote live training") is carried out by way of an interactive, remote desktop. Onsite live Face Recognition training can be carried out locally on customer premises in Kuala Lumpur or in NobleProg corporate training centers in Kuala Lumpur.
Face Recognition is also known as Facial Recognition.
NobleProg -- Your Local Training Provider
Kuala Lumpur KL Sentral
1 Sentral, Level 16, Jalan , Kuala Lumpur, malaysia, 50470
The 1 Sentral Centre is located in the northwest corner of Kuala Lumpur Sentral, a prime location in the heart of the city. A...
The 1 Sentral Centre is located in the northwest corner of Kuala Lumpur Sentral, a prime location in the heart of the city. Although 1 Sentral is just outside the central business district, Kuala Lumpur Sentral is known as a transportation hub and as one of the designated Multimedia Supercorridor (MSC) locations. A Government designated zone, the MSC is designed to leapfrog Malaysia into the information and knowledge age. The zone aims to attract companies with tax breaks and facilities such as high speed internet and proximity to the local international airport. 1 Sentral is a 30-storey office tower covering an acre and is equipped with facilities such as mini auditorium, gymnasium and recreational area. Its architecture has integrated a variety of design techniques that make it eco-friendly and aesthetically-pleasing. Restaurants, top hotels and shopping centres are all within a five- to 10-minute walk from the centre
OpenFace is Python and Torch based open-source, real-time facial recognition software based on Google's FaceNet research.
In this instructor-led, live training, participants will learn how to use OpenFace's components to create and deploy a sample facial recognition application.
By the end of this training, participants will be able to:
Work with OpenFace's components, including dlib, OpenVC, Torch, and nn4 to implement face detection, alignment, and transformation
Apply OpenFace to real-world applications such as surveillance, identity verification, virtual reality, gaming, and identifying repeat customers, etc.
Audience
Developers
Data scientists
Format of the course
Part lecture, part discussion, exercises and heavy hands-on practice
This instructor-led, live training introduces the software, hardware, and step-by-step process needed to build a facial recognition system from scratch. Facial Recognition is also known as Face Recognition.
The hardware used in this lab includes Rasberry Pi, a camera module, servos (optional), etc. Participants are responsible for purchasing these components themselves. The software used includes OpenCV, Linux, Python, etc.
By the end of this training, participants will be able to:
Install Linux, OpenCV and other software utilities and libraries on a Rasberry Pi.
Configure OpenCV to capture and detect facial images.
Understand the various options for packaging a Rasberry Pi system for use in real-world environments.
Adapt the system for a variety of use cases, including surveillance, identity verification, etc.
Format of the course
Part lecture, part discussion, exercises and heavy hands-on practice
Note
Other hardware and software options include: Arduino, OpenFace, Windows, etc. If you wish to use any of these, please contact us to arrange.
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