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. Busan onsite live Face Recognition trainings can be carried out locally on customer premises or in NobleProg corporate training centers.
Face Recognition is also known as Facial Recognition.
Busan Jungang-dong Centre is located on the 7th floor of PanOcean B/D in which many tenants are forwarding companies, shippin...
Busan Jungang-dong Centre is located on the 7th floor of PanOcean B/D in which many tenants are forwarding companies, shipping firms, and conglomerates like Hyundai marine, Woori bank, Shinhan investment, Joongang newspaper. Jungang-dong is one of the main business districts in Busan, so there are many foreign consulates, financial corporations, hotels, shipping companies, etc.
The building is situated with good visibility in the centre of the traditional CBD area in Busan,100 meters from Jungang subway, 5 minutes walk to Busan International Ferry Terminal, and 4 minutes drive to Busan KTX Station or Nampo-dong downtown area.
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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