Szczecin

Biuro Aloha, Jerzego Janosika 17, Szczecin, Poland, 71-424

The training room is fully equipped, providing all necessary amenities for participants. Additionally, it has attractive transportation connections to all strategic points of the city, facilitating access for both residents and visitors. It is located just 3 kilometers from the city center, allowing for quick access to other important urban locations and amenities.

Koszalin

Gwardia, Sportowa 34, Koszalin, Poland, 75-503

The training room is equipped with full modern amenities. It is located 3 kilometers from the city center. The facility features ample parking space for training participants, ensuring convenient access for all attendees.

Explore Our Courses

AI Facial Recognition Development for Law Enforcement

 21 Hours
This instructor-led, live training in zachodniopomorskie (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.
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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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