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. Dusseldorf 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.
NobleProg -- Your Local Training Provider
Düsseldorf
NobleProg Düsseldorf, Mindener Str. 30, Düsseldorf, germany, 40227
Overview
Our training facilities are located at Mindener Str. 30 in Düsseldorf. Our spacious training rooms are located southwest of the city centre and offer optimal training conditions for your needs.
Arrival
The NobleProg training facilities are conveniently located near the Oberbilker Strasse underground station. In the south you reach the motorway A46.
Parking
You will find numerous parking spaces around our training rooms.
Local Infrastructure
In downtown Düsseldorf you will find numerous hotels and restaurants..
This instructor-led, live training in Dusseldorf (online or onsite) is aimed at beginner-level law enforcement personnel who wish to transition from manual facial sketching to using AI tools for developing facial recognition systems.
By the end of this training, participants will be able to:
Understand the fundamentals of Artificial Intelligence and Machine Learning.
Learn the basics of digital image processing and its application in facial recognition.
Develop skills in using AI tools and frameworks to create facial recognition models.
Gain hands-on experience in creating, training, and testing facial recognition systems.
Understand ethical considerations and best practices in the use of facial recognition technology.
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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