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 trainings in Melbourne can be carried out locally on customer premises or in NobleProg corporate training centers.
Face Recognition is also known as Facial Recognition.
385 Bourke Street is located in the bustling Central Business District (CBD) and retail precinct of Melbourne's commercial hu...
385 Bourke Street is located in the bustling Central Business District (CBD) and retail precinct of Melbourne's commercial hub, making it by far the most sought after address in the City. Positioned directly opposite the Bourke street Mall, the 41 level tower houses a two level retail complex, known as the Galleria Retail Centre. Showcased underneath an impressive high glass ceiling, the retail specialty stores offer the best in giftware, fashion, food and services. The premium grade property is uniquely positioned on a 45 degree angle to the Melbourne CBD grid, providing excellent 360 degree views and has excellent access to public transport, with trams running along both Bourke and Elizabeth Streets and train and bus stations within 500 metres.
Cliftons Perth
Parmelia House, 191 St Georges Terrace, Perth, Australia, 6000
Located within the historic Bishops See precinct, it sits at the western end of Perth’s Commercial Business District
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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