Yokohama - Kannai Business Center

8F Yokohama Onoecho Building, 4-57 Onoecho, Naka-ku, Kanagawa, Yokohama, japan, 231-0015
The centre is located within a 5-minute walk from JR Kannai station and a 3-minute walk from Yokohama Blue Line Subway’s Ka...

Explore Our Courses

OpenFace: Creating Facial Recognition Systems

14 Hours
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
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Raspberry Pi + OpenCV for Facial Recognition

21 Hours
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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Testimonials (10)

examples and exercises

Kamil
Course - Introduction to Data Science and AI using Python

Machine Translated

The course is very interesting being the main focus nowdays

mohamed taher - FAB banak Egypt
Course - Introduction to Data Science and AI (using Python)

Ahmed was very interactive and didn’t mind answering any kind of questions Well presentation and smooth flow of the course

Mohamed Ghowaiba - FAB banak Egypt
Course - Introduction to Data Science and AI (using Python)

Helpful and good listener .. interactive

Ahmed El Kholy - FAB banak Egypt
Course - Introduction to Data Science and AI (using Python)

All the information presented

Jose Victor - si
Course - Artificial Intelligence (AI) for Managers

The exercises and examples presented.

Marcos - si
Course - Artificial Intelligence (AI) for Managers

Machine Translated

Machine Learning Themes

Víctor Edgar - si
Course - Artificial Intelligence (AI) for Managers

The teacher's attitude

Ivonne Guadalupe Avendaño Hernandez - si
Course - Artificial Intelligence (AI) for Managers

Machine Translated

The concepts taught were clear, practical and help a lot in getting an idea of how to use this AI & ML topic.

Miguel - si
Course - Artificial Intelligence (AI) for Managers

Machine Translated

The training definitely backfilled some of the gaps in my knowledge left by reading the OptaPlanner userguide. It gave me a good broad understanding of how to approach using OptaPlanner in our projects going forward.

Terry Strachan - Exel Computer Systems plc
Course - OptaPlanner in Practice

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