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 Kansas or in NobleProg corporate training centers in Kansas.
Face Recognition is also known as Facial Recognition.
NobleProg -- Your Local Training Provider
KS, Overland Park - Commerce Plaza
7300 West 110th Street, Commerce Plaza I, Overland Park, United States, 66210
The office in Commerce Plaza is in the heart of Overland Park, which is frequently listed as one of the best places to live and work in America. Overland Park is a nationally recognized city and has a thriving economy. It is positioned in the premier office corridor of College Boulevard in Johnson County, which has experienced rapid economic growth and is a nationally-recognized center of excellence. The office is also near the Sprint Campus in a gleaming high-rise building that's landscaped with trees. It's also well served for hotels within five minutes' walking distance, shopping malls and restaurants.
NE, Omaha - Landmark Center
1299 Farnam Street Suite 300, Omaha, United States, 68102
The venue is located on the corner of S 13th St and Famam St, with a beautiful view at American Park and just across the street from the Nebraska State Office Building.
OK, Oklahoma City - Park Avenue
101 Park Ave #1300, Oklahoma City, united states, 73102
The venue is located in the same building as Rolex and BC Clark Jewelers, just opposite of Kerr Park and the Air Force Monument.
This instructor-led, live training in Kansas (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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